diff --git a/Dockerfile b/Dockerfile
index f792361f3631761c26dc8a676e110052ed0585d5..15578e1f1183977da058e4b767f6f8b470fa67d5 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -3,14 +3,15 @@ FROM node:8 as builder
 COPY . /iv
 WORKDIR /iv
 
-ENV VERSION=test
+ENV VERSION=devNext
+ENV NODE_ENV=production
+ENV DOCKER_BUILD=true
 
 RUN npm i
 RUN npm run build-aot
 
 
 # prod container
-
 FROM node:8-alpine 
 
 ARG PORT
@@ -19,10 +20,17 @@ ENV PORT=$PORT
 RUN apk --no-cache add ca-certificates
 RUN mkdir /iv-app
 WORKDIR /iv-app
-COPY --from=builder /iv/dist .
 
-EXPOSE $PORT
+# Copy built interactive viewer
+COPY --from=builder /iv/dist/aot ./public
+
+# Copy the express server
+COPY --from=builder /iv/deploy .
 
-RUN npm i express
+# Copy the resources files needed to respond to queries
+COPY --from=builder /iv/src/res/ext ./res
+RUN npm i
+
+EXPOSE $PORT
 
 ENTRYPOINT [ "node", "server.js" ]
\ No newline at end of file
diff --git a/deploy/.gitignore b/deploy/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..20d4182a3bef0d148bce08fdadaf3999dddeeede
--- /dev/null
+++ b/deploy/.gitignore
@@ -0,0 +1,3 @@
+.env
+res/*
+raw
diff --git a/deploy/catchError.js b/deploy/catchError.js
new file mode 100644
index 0000000000000000000000000000000000000000..f1e385c3197005745ec571a62784aaf8854ca1e6
--- /dev/null
+++ b/deploy/catchError.js
@@ -0,0 +1,6 @@
+module.exports = ({code = 500, error = 'an error had occured'}, req, res, next) => {
+  /**
+   * probably use more elaborate logging?
+   */
+  res.status(code).send(error)
+}
\ No newline at end of file
diff --git a/deploy/datasets/index.js b/deploy/datasets/index.js
new file mode 100644
index 0000000000000000000000000000000000000000..70d2d38bc516f8b71f4015d7cf0211b3c7894dce
--- /dev/null
+++ b/deploy/datasets/index.js
@@ -0,0 +1,111 @@
+const express = require('express')
+const fs = require('fs')
+const path = require('path')
+const datasetsRouter = express.Router()
+
+const cachedFilePath = path.join(__dirname, '..', 'res', 'cachedKgDS.20190225.json')
+let cachedData = null
+let cachedSpaces = null
+
+fs.readFile(cachedFilePath, 'utf-8', (err, data) => {
+  if (err)
+    throw err
+  const json = JSON.parse(data)
+  cachedData = json.results.filter(ds => ds.embargoStatus.some(s => s === 'Free'))
+
+  const allPNames = cachedData.filter(v => v.parcellationRegion.length > 0).map(v => v.parcellationRegion[0].name)
+  const noPNameNoRefSpace = cachedData.filter(v => v.parcellationRegion.length === 0 && v.referenceSpaces.length === 0)
+})
+
+datasetsRouter.get('/templateName/:templateName', (req, res) => {
+  const { templateName } = req.params
+  /**
+   * temporary use cached data. in future, live fetch data and/or apply caching
+   */
+  const filteredData = cachedData.filter(ds => {
+    return templateName === 'undefined'
+      ? ds.referenceSpaces.length === 0
+      : ds.referenceSpaces.some(rs => rs.name === templateName)
+  })
+  res.status(200).send(JSON.stringify(filteredData))
+})
+
+
+const readConfigFile = (filename) => new Promise((resolve, reject) => {
+  const filepath = path.join(__dirname, '..', 'res', filename)
+  fs.readFile(filepath, 'utf-8', (err, data) => {
+    if(err) reject(err)
+    resolve(data)
+  })
+})
+
+const flattenArray = (array) => {
+  return array.filter(item => item.children.length === 0).concat(
+    ...array.filter(item => item.children.length > 0).map(item => flattenArray(item.children))
+  )
+}
+
+let juBrain = null
+let shortBundle = null
+let longBundle = null
+
+readConfigFile('colin.json')
+  .then(data => JSON.parse(data))
+  .then(json => {
+    juBrain = flattenArray(json.parcellations[0].regions)
+  })
+  .catch(console.error)
+
+readConfigFile('MNI152.json')
+  .then(data => JSON.parse(data))
+  .then(json => {
+    longBundle = flattenArray(json.parcellations[0].regions)
+    shortBundle = flattenArray(json.parcellations[1].regions)
+  })
+  .catch(console.error)
+
+datasetsRouter.get('/parcellationName/:parcellationName', (req, res) => {
+  const { parcellationName } = req.params
+  let returnArr
+  switch (parcellationName) {
+    case 'JuBrain Cytoarchitectonic Atlas':
+      returnArr = juBrain
+        ? cachedData
+          .filter(ds => !/infant/i.test(ds.name))
+          .filter(ds =>  
+            ds.parcellationRegion.length > 0 &&
+            ds.parcellationRegion.some(pr => {
+              const regex = new RegExp(pr.name)
+              return juBrain.some(juBR => regex.test(juBR.name))
+            }))
+        : []
+      break;
+    case 'Fibre Bundle Atlas - Long Bundle':
+      returnArr = longBundle
+        ? cachedData
+            .filter(ds =>  
+              ds.parcellationRegion.length > 0 &&
+              ds.parcellationRegion.some(pr => {
+                const regex = new RegExp(pr.name)
+                return longBundle.some(lbr => regex.test(lbr.name))
+              }))
+        : []
+      break;
+    case 'Fibre Bundle Atlas - Short Bundle':
+      returnArr = shortBundle
+      ? cachedData
+          .filter(ds =>  
+            ds.parcellationRegion.length > 0 &&
+            ds.parcellationRegion.some(pr => {
+              const regex = new RegExp(pr.name)
+              return shortBundle.some(sbr => regex.test(sbr.name))
+            }))
+      : []
+      break;
+    default:
+      returnArr = []
+  }
+  res.status(200).send(JSON.stringify(returnArr))
+})
+
+module.exports = datasetsRouter
\ No newline at end of file
diff --git a/deploy/nehubaConfig/index.js b/deploy/nehubaConfig/index.js
new file mode 100644
index 0000000000000000000000000000000000000000..0e716e53fa61864f318cfbb60411ef28e3c2a6fb
--- /dev/null
+++ b/deploy/nehubaConfig/index.js
@@ -0,0 +1,17 @@
+const express = require('express')
+const path = require('path')
+const fs = require('fs')
+
+const nehubaConfigRouter = express.Router()
+
+nehubaConfigRouter.get('/:configId', (req, res, next) => {
+  const { configId } = req.params
+  const configFilePath = path.join(__dirname, '..', 'res', `${configId}.json`)
+  fs.readFile(configFilePath, 'utf-8', (error, data) => {
+    if (error) 
+      return next({code: 500, error})
+    res.status(200).send(data)
+  })
+})
+
+module.exports = nehubaConfigRouter
\ No newline at end of file
diff --git a/deploy/package.json b/deploy/package.json
new file mode 100644
index 0000000000000000000000000000000000000000..fe22fd3a98bad52e51abf25f7763a6e9105293f0
--- /dev/null
+++ b/deploy/package.json
@@ -0,0 +1,20 @@
+{
+  "name": "deploy",
+  "version": "1.0.0",
+  "description": "",
+  "main": "index.js",
+  "scripts": {
+    "start": "node server.js"
+  },
+  "keywords": [],
+  "author": "",
+  "license": "ISC",
+  "dependencies": {
+    "express": "^4.16.4",
+    "openid-client": "^2.4.5"
+  },
+  "devDependencies": {
+    "cors": "^2.8.5",
+    "dotenv": "^6.2.0"
+  }
+}
diff --git a/deploy/server.js b/deploy/server.js
new file mode 100644
index 0000000000000000000000000000000000000000..6dd4b914fbb81239e450c1561a6219cc44eb0f18
--- /dev/null
+++ b/deploy/server.js
@@ -0,0 +1,31 @@
+const path = require('path')
+const express = require('express')
+const app = express()
+
+app.disable('x-powered-by')
+
+if (process.env.NODE_ENV !== 'production') {
+  require('dotenv').config()
+  app.use(require('cors')())
+}
+
+const templateRouter = require('./templates')
+const nehubaConfigRouter = require('./nehubaConfig')
+const datasetRouter = require('./datasets')
+const catchError = require('./catchError')
+
+const publicPath = process.env.DOCKER_BUILD
+  ? path.join(__dirname, 'public')
+  : path.join(__dirname, '..', 'dist', 'aot')
+
+app.use('/templates', templateRouter)
+app.use('/nehubaConfig', nehubaConfigRouter)
+app.use('/datasets', datasetRouter)
+
+app.use(catchError)
+
+app.use(express.static(publicPath))
+
+const PORT = process.env.PORT || 3000
+
+app.listen(PORT, () => console.log(`listening on port ${PORT}`))
\ No newline at end of file
diff --git a/deploy/templates/index.js b/deploy/templates/index.js
new file mode 100644
index 0000000000000000000000000000000000000000..e22658cd590a6cc60e565c61e04863779f9e938e
--- /dev/null
+++ b/deploy/templates/index.js
@@ -0,0 +1,41 @@
+const router = require('express').Router()
+const query = require('./query')
+const path = require('path')
+/**
+ * root path fetches all templates
+ */
+router.get('/', (req, res, next) => {
+  const baseUrl = req.baseUrl
+  query.getAllTemplates()
+    .then(templates => {
+      const templatesRes = templates.map(v => path.join(baseUrl.slice(1), v))
+      res.status(200).send(JSON.stringify(templatesRes))
+    })
+    .catch(error => next({
+      code: 500,
+      error
+    }))
+})
+
+router.get('/:template', (req, res, next) => {
+  const { template } = req.params
+  query.getAllTemplates()
+    .then(templates => {
+      if (templates.indexOf(template) < 0) 
+        return next({
+          code : 404,
+          error: 'template not in the list supported'
+        })
+      return query.getTemplate(template)
+    })
+    .then(data => {
+      if (data)
+        res.status(200).send(data)
+    })
+    .catch(error => next({
+      code: 500,
+      error
+    }))
+})
+
+module.exports = router
\ No newline at end of file
diff --git a/deploy/templates/query.js b/deploy/templates/query.js
new file mode 100644
index 0000000000000000000000000000000000000000..485e71c5726084526a16321caeb3d1b60dfdb95f
--- /dev/null
+++ b/deploy/templates/query.js
@@ -0,0 +1,27 @@
+const fs = require('fs')
+const path = require('path')
+
+exports.getAllTemplates = () => new Promise((resolve, reject) => {
+  
+  /**
+   * TODO temporary. Need to query KG or something else for this data in the future
+   */
+  const templates = [
+    // 'infant',
+    'bigbrain',
+    'colin',
+    'MNI152',
+    'waxholmRatV2_0',
+    'allenMouse'
+  ]
+  resolve(templates)
+})
+
+exports.getTemplate = (template) => new Promise((resolve, reject) => {
+
+  const filePath = path.join(__dirname, '..', 'res', `${template}.json`)
+  fs.readFile(filePath, 'utf-8', (err, data) => {
+    if (err) reject(err)
+    resolve(data)
+  })
+})
\ No newline at end of file
diff --git a/dist/server.js b/dist/server.js
deleted file mode 100644
index 4976f328c8787fe5e1f9f13211fb0bb3a394ac5b..0000000000000000000000000000000000000000
--- a/dist/server.js
+++ /dev/null
@@ -1,9 +0,0 @@
-const express = require('express')
-const app = express()
-const path = require('path')
-
-app.use(express.static( path.resolve(__dirname, 'aot')))
-
-const PORT = process.env.PORT || 3001
-
-app.listen(PORT, () => console.log(`listening on port ${PORT}`))
\ No newline at end of file
diff --git a/src/atlasViewer/atlasViewer.constantService.service.ts b/src/atlasViewer/atlasViewer.constantService.service.ts
index d99fa429dc6819c5541b65e9185426a2191fe76e..fa08fc8bf1916101db58fb497de6c69a8302f883 100644
--- a/src/atlasViewer/atlasViewer.constantService.service.ts
+++ b/src/atlasViewer/atlasViewer.constantService.service.ts
@@ -48,8 +48,23 @@ export class AtlasViewerConstantsServices{
       prevLandmarks.length === newLandmarks.length
   }
 
+  public backendUrl = BACKEND_URL
+
   /* to be provided by KG in future */
-  public templateUrls = [
+  public templateUrlsPr : Promise<string[]> = new Promise((resolve, reject) => {
+    fetch(`${this.backendUrl}templates`)
+      .then(res => res.json())
+      .then(arr => {
+        this.templateUrls = arr
+        return arr
+      })
+      .then(resolve)
+      .catch(reject)
+  })
+
+  public templateUrls = Array(100)
+
+  private _templateUrls = [
     // 'res/json/infant.json',
     'res/json/bigbrain.json',
     'res/json/colin.json',
@@ -74,7 +89,7 @@ export class AtlasViewerConstantsServices{
       ]
     ],
     [
-      'Allen Mouse Brain Atlas',
+      'Allen adult mouse brain reference atlas V3 Brain Atlas',
       [
         'res/json/allenAggregated.json'
       ]
diff --git a/src/atlasViewer/atlasViewer.dataService.service.ts b/src/atlasViewer/atlasViewer.dataService.service.ts
index 872d0e9c7ed6ad95484f174aa618d2fd8f9f7ab0..5eb68ec144ff33bfeb7680d51d285b1724f2155f 100644
--- a/src/atlasViewer/atlasViewer.dataService.service.ts
+++ b/src/atlasViewer/atlasViewer.dataService.service.ts
@@ -1,8 +1,8 @@
-import { Injectable, OnDestroy, OnInit } from "@angular/core";
+import { Injectable, OnDestroy } from "@angular/core";
 import { Store, select } from "@ngrx/store";
 import { ViewerStateInterface, FETCHED_TEMPLATE, DataEntry, FETCHED_DATAENTRIES, safeFilter, FETCHED_SPATIAL_DATA, UPDATE_SPATIAL_DATA } from "../services/stateStore.service";
 import { map, distinctUntilChanged } from "rxjs/operators";
-import { Subscription } from "rxjs";
+import { Subscription, combineLatest } from "rxjs";
 import { AtlasViewerConstantsServices } from "./atlasViewer.constantService.service";
 import { PluginManifest } from "./atlasViewer.pluginService.service";
 
@@ -36,34 +36,37 @@ export class AtlasViewerDataService implements OnDestroy{
     private store : Store<ViewerStateInterface>,
     private constantService : AtlasViewerConstantsServices
   ){
-    this.constantService.templateUrls.map(url => 
-      this.constantService.raceFetch(url)
-        .then(res => res.json())
-        .then(json => new Promise((resolve, reject) => {
-          if(json.nehubaConfig)
-            resolve(json)
-          else if(json.nehubaConfigURL)
-            this.constantService.raceFetch(json.nehubaConfigURL)
-              .then(res => res.json())
-              .then(json2 => resolve(
-                Object.assign({}, json, { nehubaConfig: json2 })
-              ))
-              .catch(reject)
-          else
-            reject('neither nehubaConfig nor nehubaConfigURL defined')
-        }))
-        .then(json => this.store.dispatch({
-          type: FETCHED_TEMPLATE,
-          fetchedTemplate: json
-        }))
-        .catch(e => {
-          console.warn('fetching template url failed', e)
-          this.store.dispatch({
-            type: FETCHED_TEMPLATE,
-            fetchedTemplate: null
-          })
-        })
-      )
+    this.constantService.templateUrlsPr
+      .then(urls => 
+        urls.map(url => 
+          this.constantService.raceFetch(`${this.constantService.backendUrl}${url}`)
+            .then(res => res.json())
+            .then(json => new Promise((resolve, reject) => {
+              if(json.nehubaConfig)
+                resolve(json)
+              else if(json.nehubaConfigURL)
+                this.constantService.raceFetch(`${this.constantService.backendUrl}${json.nehubaConfigURL}`)
+                  .then(res => res.json())
+                  .then(json2 => resolve({
+                      ...json,
+                      nehubaConfig: json2
+                    }))
+                  .catch(reject)
+              else
+                reject('neither nehubaConfig nor nehubaConfigURL defined')
+            }))
+            .then(json => this.store.dispatch({
+              type: FETCHED_TEMPLATE,
+              fetchedTemplate: json
+            }))
+            .catch(e => {
+              console.warn('fetching template url failed', e)
+              this.store.dispatch({
+                type: FETCHED_TEMPLATE,
+                fetchedTemplate: null
+              })
+            })
+        ))
 
     this.init()
   }
@@ -89,7 +92,7 @@ export class AtlasViewerDataService implements OnDestroy{
     /* TODO future for template space? */
     const filterTemplateSpace = templateSpace == 'MNI Colin 27' ? 
       'datapath:metadata/sEEG-sample.json' :
-        templateSpace == 'Waxholm Rat V2.0' ?
+        templateSpace == 'Waxholm Space rat brain atlas v.2.0' ?
         'datapath:metadata/OSLO_sp_data_rev.json' :
           null
     
@@ -117,7 +120,7 @@ export class AtlasViewerDataService implements OnDestroy{
           })
         })
         .catch(console.error)
-    }else if (templateSpace === 'Allen Mouse'){
+    }else if (templateSpace === 'Allen adult mouse brain reference atlas V3'){
       return Promise.all([
         // 'res/json/allen3DVolumeAggregated.json',
         'res/json/allenTestPlane.json',
@@ -135,7 +138,7 @@ export class AtlasViewerDataService implements OnDestroy{
           })
         })
         .catch(console.error)
-    }else if (templateSpace === 'Waxholm Rat V2.0'){
+    }else if (templateSpace === 'Waxholm Space rat brain atlas v.2.0'){
       return Promise.all([
         // fetch('res/json/waxholmPlaneAggregatedData.json').then(res => res.json()),
         fetch('res/json/camillaWaxholmPointsAggregatedData.json').then(res => res.json())
@@ -194,23 +197,41 @@ export class AtlasViewerDataService implements OnDestroy{
       })
     }
 
-    const fetchData = (parcellationName : string) => {
-      const urlArrays = this.constantService.mapParcellationNameToFetchUrl.get(parcellationName)
-      urlArrays ?
-        Promise.all(urlArrays.map(url=>fetch(url).then(res=>res.json())))
-          .then(arr=>dispatchData(arr))
-          .catch(console.warn) :
-        dispatchData([])
+    const fetchData = (templateName : string, parcellationName: string) => {
+      dispatchData([])
+      const encodedTemplateName = encodeURI(templateName)
+      const encodedParcellationName = encodeURI(parcellationName)
+      Promise.all([
+        fetch(`${this.constantService.backendUrl}datasets/templateName/${encodedTemplateName}`)
+          .then(res => res.json()),
+        fetch(`${this.constantService.backendUrl}datasets/parcellationName/${encodedParcellationName}`)
+          .then(res => res.json())
+      ])
+        .then(arr => [...arr[0], ...arr[1]])
+        .then(arr => arr.reduce((acc, item) => {
+          const newMap = new Map(acc)
+          return newMap.set(item.name, item)
+        }, new Map()))
+        .then(map => Array.from(map.values()))
+        .then(dispatchData)
+        .catch(console.warn)
     }
-      
+
     this.subscriptions.push(
-      this.store.pipe(
-        select('viewerState'),
-        safeFilter('parcellationSelected'),
-        map(({parcellationSelected})=>(parcellationSelected.name)),
-        distinctUntilChanged()
-      )
-        .subscribe(fetchData)
+      combineLatest(
+        this.store.pipe(
+          select('viewerState'),
+          safeFilter('templateSelected'),
+          map(({templateSelected})=>(templateSelected.name)),
+          distinctUntilChanged()
+        ),
+        this.store.pipe(
+          select('viewerState'),
+          safeFilter('parcellationSelected'),
+          map(({parcellationSelected})=>(parcellationSelected.name)),
+          distinctUntilChanged()
+        )
+      ).subscribe((param : [string, string] ) => fetchData(param[0], param[1]))
     )
   }
 
diff --git a/src/components/components.module.ts b/src/components/components.module.ts
index 7f7f4f19cbede9efcc7f03dc13061878d19086d2..b7bcd03b86b97857e7fb1b007b967a1dc296914a 100644
--- a/src/components/components.module.ts
+++ b/src/components/components.module.ts
@@ -24,6 +24,7 @@ import { FitlerRowsByVisibilityPipe } from './flatTree/filterRowsByVisibility.pi
 import { AppendSiblingFlagPipe } from './flatTree/appendSiblingFlag.pipe';
 import { ClusteringPipe } from './flatTree/clustering.pipe';
 import { TimerComponent } from './timer/timer.component';
+import { PillComponent } from './pill/pill.component';
 
 
 @NgModule({
@@ -43,6 +44,7 @@ import { TimerComponent } from './timer/timer.component';
     ToastComponent,
     FlatTreeComponent,
     TimerComponent,
+    PillComponent,
 
     /* directive */
     HoverableBlockDirective,
@@ -71,6 +73,7 @@ import { TimerComponent } from './timer/timer.component';
     ToastComponent,
     FlatTreeComponent,
     TimerComponent,
+    PillComponent,
 
     SearchResultPaginationPipe,
     TreeSearchPipe,
diff --git a/src/components/pagination/pagination.style.css b/src/components/pagination/pagination.style.css
index 2b06f6363c0b0d943f788e8be0077da07b8e75a2..57325bbb9d4491d42cdec4b81cf6fce16b3fc2e1 100644
--- a/src/components/pagination/pagination.style.css
+++ b/src/components/pagination/pagination.style.css
@@ -70,4 +70,9 @@ div.btn.btn-primary:before
   opacity : 0.1;
 
   pointer-events: none;
+}
+
+.pagination-control
+{
+  font-size:80%;
 }
\ No newline at end of file
diff --git a/src/components/pill/pill.component.ts b/src/components/pill/pill.component.ts
new file mode 100644
index 0000000000000000000000000000000000000000..4764320b46ec6782e56266e4489bf0d66d51b7b6
--- /dev/null
+++ b/src/components/pill/pill.component.ts
@@ -0,0 +1,27 @@
+import { Component, Input, Output, EventEmitter } from "@angular/core";
+
+@Component({
+  selector: 'pill-component',
+  templateUrl: './pill.template.html',
+  styleUrls: [
+    './pill.style.css'
+  ]
+})
+
+export class PillComponent{
+  @Input() title: string = 'Untitled Pill'
+  @Input() showClose: boolean = true
+  @Output() pillClicked: EventEmitter<boolean> = new EventEmitter()
+  @Output() closeClicked: EventEmitter<boolean> = new EventEmitter()
+
+  @Input() containerStyle: any = {
+    backgroundColor: 'grey'
+  }
+  @Input() closeBtnStyle: any = {
+    backgroundColor: 'lightgrey'
+  }
+
+  close() {
+    this.closeClicked.emit(true)
+  }
+}
\ No newline at end of file
diff --git a/src/components/pill/pill.style.css b/src/components/pill/pill.style.css
new file mode 100644
index 0000000000000000000000000000000000000000..7fae3ae45d04164d0e1482c3b02564b850a2f20f
--- /dev/null
+++ b/src/components/pill/pill.style.css
@@ -0,0 +1,32 @@
+.pill-container
+{
+  padding: 0.2em 1em;
+  margin-left: 0.2em;
+  border-radius: 1em;
+  display: flex;
+  align-items: center;
+}
+
+.pill-title
+{
+  flex: 0 0 auto;
+}
+
+.pill-close
+{
+  flex: 0 0 auto;
+  width:1.4em;
+  height: 1.4em;
+  font-size:0.8em;
+  padding: 0.2em;
+  border-radius: 0.7em;
+  box-sizing: border-box;
+
+  margin-left: 0.4em;
+  margin-right: -0.8em;
+}
+
+:host
+{
+  display: inline-block;
+}
\ No newline at end of file
diff --git a/src/components/pill/pill.template.html b/src/components/pill/pill.template.html
new file mode 100644
index 0000000000000000000000000000000000000000..0900ed2148bdaac8e0de9169dbf4792f5877f4c7
--- /dev/null
+++ b/src/components/pill/pill.template.html
@@ -0,0 +1,15 @@
+<div
+  [ngStyle]="containerStyle"
+  class="pill-container">
+  <span
+    class="pill-title">
+    {{ title }}
+  </span>
+  <span
+    [ngStyle]="closeBtnStyle"
+    class="pill-close"
+    (click)="close()"
+    *ngIf="showClose">
+    <i class="glyphicon glyphicon-remove"></i>
+  </span>
+</div>
\ No newline at end of file
diff --git a/src/res/ext/allen3DReconAggregated.json b/src/res/ext/allen3DReconAggregated.json
index d0e5e966552685c8f4ec1ad88f27443db8b07819..9e35efd7ce68e42a57107a3108d5432163e552ad 100644
--- a/src/res/ext/allen3DReconAggregated.json
+++ b/src/res/ext/allen3DReconAggregated.json
@@ -1 +1 @@
-[{"name":"Tissue Contour idx 0 - 0","templateSplace":"Allen Mouse","geometry":{"type":"point","space":"real","position":[-2.8549999999999995,-1.2767400000000002,-1.0561100000000003]}},{"name":"Tissue Contour idx 0 - 1","templateSplace":"Allen Mouse","geometry":{"type":"point","space":"real","position":[-2.8549999999999995,-0.4450000000000003,-1.0699199999999998]}},{"name":"Tissue Contour idx 0 - 2","templateSplace":"Allen Mouse","geometry":{"type":"point","space":"real","position":[-2.8549999999999995,0.049920000000000186,-1.0630199999999999]}},{"name":"Tissue Contour idx 0 - 3","templateSplace":"Allen Mouse","geometry":{"type":"point","space":"real","position":[-2.8549999999999995,0.7441800000000001,-1.0423]}},{"name":"Tissue Contour idx 0 - 4","templateSplace":"Allen Mouse","geometry":{"type":"point","space":"real","position":[-2.8549999999999995,1.1634799999999998,-0.9387300000000005]}},{"name":"Tissue Contour idx 0 - 5","templateSplace":"Allen Mouse","geometry":{"type":"point","space":"real","position":[-2.8549999999999995,1.7890100000000002,-0.69705]}},{"name":"Tissue Contour idx 0 - 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\ No newline at end of file
diff --git a/src/res/ext/allen3DVolumeAggregated.json b/src/res/ext/allen3DVolumeAggregated.json
index cc4bb70bf31b1e95598ec8ed51a5914429c70dfa..ade5283cc44cfbe2682555ef84ca3dd6b4bd9768 100644
--- a/src/res/ext/allen3DVolumeAggregated.json
+++ b/src/res/ext/allen3DVolumeAggregated.json
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/src/res/ext/allenAggregated.json b/src/res/ext/allenAggregated.json
index c4c1c2f0f0708526aec8ebe09418ad32ca55efc9..8e04c3304331c484a701351bdf5ecb6a2b382845 100644
--- a/src/res/ext/allenAggregated.json
+++ b/src/res/ext/allenAggregated.json
@@ -1 +1 @@
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diff --git a/src/res/ext/allenMouse.json b/src/res/ext/allenMouse.json
index f49dbb4a6ecdeaeb31be89f202789ea0e1a39dd4..36678f5a884542a246334e430ac7200f4853e37d 100644
--- a/src/res/ext/allenMouse.json
+++ b/src/res/ext/allenMouse.json
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diff --git a/src/res/ext/allenTestAggregated.json b/src/res/ext/allenTestAggregated.json
index a2a6561648f4dce323a248d8347a34a0f6afb861..c963b8ccc3f7d0e82040adbe3db112333141a013 100644
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diff --git a/src/res/ext/allenTestPlane.json b/src/res/ext/allenTestPlane.json
index c9087d74295d94fe39d4182badda5ab7841baf37..9598e75886e6d488915dbf3601ae237014f75858 100644
--- a/src/res/ext/allenTestPlane.json
+++ b/src/res/ext/allenTestPlane.json
@@ -1 +1 @@
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\ No newline at end of file
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\ No newline at end of file
diff --git a/src/res/ext/cachedKgDS.20190225.json b/src/res/ext/cachedKgDS.20190225.json
new file mode 100644
index 0000000000000000000000000000000000000000..dbb4b5b9ec588de8031adafc9d2fb739e972ab59
--- /dev/null
+++ b/src/res/ext/cachedKgDS.20190225.json
@@ -0,0 +1,23551 @@
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+        }
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+      ],
+      "contributors": [
+        "Eickhoff, Simon B.",
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Grill-Spector, Kalanit",
+        "Bludau, Sebastian",
+        "Schleicher, Axel",
+        "Mohlberg, Hartmut",
+        "Caspers, Julian",
+        "Weiner, Kevin S.",
+        "Lorenz, Simon"
+      ],
+      "kgReference": [
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+        }
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+      ],
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+      "custodians": [
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+      "parcellationRegion": [
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+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
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+      "publications": [
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+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Isthmus Cingulate and Precuneus gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
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+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
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+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
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+      "publications": [
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+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Pavone, Francesco S."
+      ],
+      "description": "The dataset contains the complete reconstruction of the cerebellum from an L7-GFP mouse (PND 10), where all Purkinje cells are fluorescently labeled. The dataset includes raw imaging data obtained with confocal light sheet microscopy of cleared sample and cell localization (position of somata expressed as xyz coordinates).",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Purkinje cell distribution in mouse cerebellum",
+      "files": [],
+      "contributors": [
+        "Pavone, Francesco S.",
+        "Silvestri, Ludovico"
+      ],
+      "kgReference": [
+        "10.25493/76F0-87N"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area hOc4lp (LOC) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area hOc4lp (LOC). The probability map of Area hOc4lp (LOC) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-hOc4lp.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area hOc4lp (LOC)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area hOc4lp (LOC)",
+      "files": [
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+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-hOc4lp.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Malikovic, Aleksandar",
+        "Zilles, Karl",
+        "Eickhoff, Simon B.",
+        "Palomero-Gallagher, Nicola",
+        "Kujovic, Milenko",
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [
+        "10.25493/W4H2-WTM"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitecture of the human lateral occipital cortex: mapping of two extrastriate areas hOc4la and hOc4lp",
+          "cite": "Malikovic, A., Amunts, K., Schleicher, A., Mohlberg, H., Kujovic, M., Palomero-Gallagher, N., … Zilles, K. (2015). Cytoarchitecture of the human lateral occipital cortex: mapping of two extrastriate areas hOc4la and hOc4lp. Brain Structure and Function, 221(4), 1877–1897. ",
+          "doi": "10.1007/s00429-015-1009-8"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Weber, Bruno"
+      ],
+      "description": "The goal of the study is to produce the first high resolution, 3D reconstruction of the entire macrostructure and vascular system of the rat/mouse brain. To that end synchrotron radiation-based X-ray microscopy images were collected. Then the data is translated into 3D mesh and volumetric models (graph).  \nThis dataset contains the model of part of cortical vasculature of the rat brain as a graph structure (discrete mathematics).  \nThe data is a derived dataset using computational methods from the dataset “3D high resolution SRXTM image data of cortical vasculature of rat brain” ([doi: 10.25493/HCPQ-MY8](https://doi.org/10.25493/HCPQ-MY8)).",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Graphical representation of rat cortical vasculature reconstructed from high resolution 3D SRXTM data.",
+      "files": [],
+      "contributors": [
+        "Weber, Bruno",
+        "Menze, Bjoern H.",
+        "Székely, Gábor",
+        "Hirsch, Sven",
+        "Schneider, Matthias"
+      ],
+      "kgReference": [
+        "10.25493/K243-13K"
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+      "publications": [
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+          "cite": "Schneider, M., Hirsch, S., Weber, B., Székely, G., & Menze, B. H. (2015). Joint 3-D vessel segmentation and centerline extraction using oblique Hough forests with steerable filters. Medical Image Analysis, 19(1), 220–249. ",
+          "doi": "10.1016/j.media.2014.09.007"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
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+      "description": "This dataset contains the distinct architectonic Area 5L (SPL) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area 5L (SPL). The probability map of Area 5L (SPL) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-5L.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
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+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 5L (SPL)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area 5L (SPL)",
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Hermann, K.",
+        "Eickhoff, Simon B.",
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Hoemke, L.",
+        "Amunts, Katrin",
+        "Scheperjans, Filip"
+      ],
+      "kgReference": [
+        "10.25493/A5V4-HFH"
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+      "publications": [
+        {
+          "name": "Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Eickhoff, S. B., Hoemke, L., Mohlberg, H., Hermann, K., Amunts, K., & Zilles, K. (2008). Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex. Cerebral Cortex, 18(9), 2141–2157. ",
+          "doi": "10.1093/cercor/bhm241"
+        },
+        {
+          "name": "Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Hermann, K., Eickhoff, S. B., Amunts, K., Schleicher, A., & Zilles, K. (2007). Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex. Cerebral Cortex, 18(4), 846–867. ",
+          "doi": "10.1093/cercor/bhm116"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
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+        "Mohlberg, Hartmut",
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+        "Saal, Martin",
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+        "Caspers, Svenja",
+        "Mohlberg, Hartmut",
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+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
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+        "Costantini, Irene",
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+        "Becuwe-Desmidt, Séverine",
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+          "cite": "Pinho, A. L., Amadon, A., Ruest, T., Fabre, M., Dohmatob, E., Denghien, I., … Thirion, B. (2018). Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping. Scientific Data, 5, 180105. ",
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+      "description": "This dataset contains the distinct architectonic Area Fo2 (OFC) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Area Fo2 (OFC). The probability map of Area Fo2 (OFC) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-Fo2.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area Fo2 (OFC)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area Fo2 (OFC)",
+      "files": [
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-Fo2.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Mohlberg, Hartmut",
+        "Amunts, Katrin",
+        "Bludau, Sebastian",
+        "Eickhoff, Simon B.",
+        "Gerboga, Fatma",
+        "Schleicher, Axel",
+        "Palomero-Gallagher, Nicola",
+        "Zilles, Karl",
+        "Henssen, Anton"
+      ],
+      "kgReference": [
+        "10.25493/N14D-JQT"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitecture and probability maps of the human medial orbitofrontal cortex",
+          "cite": "Henssen, A., Zilles, K., Palomero-Gallagher, N., Schleicher, A., Mohlberg, H., Gerboga, F., … Amunts, K. (2016). Cytoarchitecture and probability maps of the human medial orbitofrontal cortex. Cortex, 75, 87–112. ",
+          "doi": "10.1016/j.cortex.2015.11.006"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
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+      "description": "Transgenic mice carrying the Arctic (E693G) and Swedish (KM670/6701NL) amyloid-b precursor protein (AβPP) develop amyloid-beta (Aβ) deposits in the brain that resemble Alzheimer’s disease neuropathology. The tg-ArcSwe atlas provides access to Aβx-40 immunolabeled histological section images from representative 12 month old tg-ArcSwe mice (Lord et al., Neurobiol. Aging 27:67-77, 2006), showing the morphology and spatial distribution of Aβx-40 plaque deposits across the brain. Analyses show that plaques are primarily distributed in the cerebral cortex, hippocampus, and thalamus. The average Aβ burden in the cortex and hippocampus is similar across animals, with coefficients of variance of 22% and 25%, respectively (Lillehaug et al., Neurobiol Aging 35:556-564, 2014).",
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+        "Creative Commons Attribution-ShareAlike 4.0 International"
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+        "Free"
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+      "license": [
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+      "name": "Brainwide distribution and variance of amyloid-beta deposits in tg-ArcSwe mice",
+      "files": [],
+      "contributors": [
+        "Lillehaug, Sveinung",
+        "Bjaalie, Jan G.",
+        "Leergaard, Trygve B.",
+        "Syverstad, Gry H.",
+        "Nilsson, Lars N.G.",
+        "Torp, Reidun"
+      ],
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+          "cite": "",
+          "doi": "10.1016/j.neurobiolaging.2013.09.013"
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+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Sanchez-Vives, Maria"
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+      "description": "Local field potentials were recorded in the cerebral cortex of a mouse model of Fragile X syndrome during slow wave activity under ketamine anesthesia. Different parameters of the recorded signal were compared to those of wild type littermates to assess functional biomarkers characterizing Fragile X syndrome. The approach was similar to that in previous publications of our group (Castano-Prat et al., 2017; Ruiz-Mejias et al., 2016).\n\n**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
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+        "Embargoed"
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+      ],
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+      "name": "Cortical recordings of the Fmr1KO mouse model of Fragile X syndrome during slow wave activity",
+      "files": [],
+      "contributors": [
+        "Castano-Prat, Patricia",
+        "Sanchez-Vives, Maria"
+      ],
+      "kgReference": [
+        "10.25493/5VDM-SHH"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Middle Temporal and Supramarginal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
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+        "Free"
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+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_MT-SM_0"
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_MT-SM_0.nii",
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+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area 4p using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp, pr, ar\n\nkainate (glutamate; [³H]kainate): fp, pr, ar\n\nNMDA (glutamate; [³H]MK-801): fp, pr, ar\n\nmGluR2/3 (glutamate; [³H] LY 341 495): pr, ar\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp, pr, ar\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp, pr, ar\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp, pr, ar\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp, pr, ar\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp, pr, ar\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp, pr, ar\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp, pr, ar\n\nα₁ (noradrenalin; [³H]prazosin): fp, pr, ar\n\nα₂ (noradrenalin; [³H]UK-14,304): fp, pr, ar\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp, pr, ar\n\n5-HT₂ (serotonin; [³H]ketanserin): fp, pr, ar\n\nD₁ (dopamine; [³H]SCH23390): fp, pr, ar\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 4p"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area 4p",
+      "files": [
+        {
+          "byteSize": 180,
+          "name": "4p_ar_examples.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_4p/4p_ar_examples.zip",
+          "contentType": "application/zip"
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+          "name": "4p_fp_20171202.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_4p/4p_fp_20171202.xlsx",
+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        },
+        {
+          "byteSize": 44096,
+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        },
+        {
+          "byteSize": 418851,
+          "name": "4p_pr_examples.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_4p/4p_pr_examples.zip",
+          "contentType": "application/zip"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike"
+      ],
+      "kgReference": [
+        "10.25493/J5JR-YH0"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Jankowsky, Joanna L."
+      ],
+      "description": "Bright-field microscopy images of serial horizontal brain sections showing Pituitary homeobox 3 (Pitx3) promoter expression in a bigenic Pitx3-tetracycline-transactivator (tTA) mouse brain (case 5154, adult female), using a driver-reporter construct in which the Pitx3-tTA promoter regulates the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, which is visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Our data show that the Pitx3-tTA promoter is spatially restricted to the substantia nigra, ventral tegmental area, and a few other regions.",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Pituitary homeobox 3 tetracycline-transactivator expression: horizontal sections (case 5154)",
+      "files": [],
+      "contributors": [
+        "Puchades, Maja A.",
+        "Lillehaug, Sveinung",
+        "Yetman, Michael J.",
+        "Jankowsky, Joanna L.",
+        "Bjaalie, Jan G.",
+        "Checinska, Martyna M.",
+        "Leergaard, Trygve B."
+      ],
+      "kgReference": [
+        "10.25493/2382-AYM"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "D'Angelo, Egidio"
+      ],
+      "description": "Study and characterization of the intrinsic properties of different cerebellar neuronal types.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Recordings of passive cellular parameters of cerebellar neurons",
+      "files": [],
+      "contributors": [
+        "Prestori, Francesca",
+        "Tognolina, Marialuisa",
+        "D'Angelo, Egidio",
+        "Soda, Teresa",
+        "Locatelli, Francesca"
+      ],
+      "kgReference": [
+        "10.25493/MVHQ-4YA"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Merchan-Perez, Angel"
+      ],
+      "description": "\n**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [],
+      "embargoStatus": [
+        "Embargoed"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Data on synapses in the somatosensory cortex of the adult mouse, obtained with three-dimensional electron microscopy (FIB-SEM).",
+      "files": [],
+      "contributors": [
+        "Turegano, Marta",
+        "Rodriguez, Rodrigo",
+        "Merchan-Perez, Angel",
+        "DeFelipe, Javier"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Caudal Anterior Cingulate and Precuneus gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_CAC-PrCu_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_CAC-PrCu_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
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+          "byteSize": 68240520,
+          "name": "lh_CAC-PrCu_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_CAC-PrCu_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area 3b using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp, pr, ar\n\nkainate (glutamate; [³H]kainate): fp, pr, ar\n\nNMDA (glutamate; [³H]MK-801): fp, pr, ar\n\nmGluR2/3 (glutamate; [³H] LY 341 495): fp, pr, ar\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp, pr, ar\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp, pr, ar\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp, pr, ar\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp, pr, ar\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp, pr, ar\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp, pr, ar\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp, pr, ar\n\nα₁ (noradrenalin; [³H]prazosin): fp, pr, ar\n\nα₂ (noradrenalin; [³H]UK-14,304): fp, pr, ar\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp, pr, ar\n\n5-HT₂ (serotonin; [³H]ketanserin): fp, pr, ar\n\nD₁ (dopamine; [³H]SCH23390): fp, pr, ar\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 3b"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area 3b",
+      "files": [
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+          "byteSize": 410091,
+          "name": "3b_pr_examples.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_3b/3b_pr_examples.zip",
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+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike"
+      ],
+      "kgReference": [
+        "10.25493/TZBY-96W"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        }
+      ]
+    },
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+        "NIFTI"
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+        {
+          "name": "MNI Colin 27"
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+      ],
+      "custodians": [
+        "Amunts, Katrin"
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+      "description": "This dataset contains the distinct architectonic Area hOc3v (LingG) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area hOc3v (LingG). The probability map of Area hOc3v (LingG) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-hOc3v.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area hOc3v (LingG)"
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+      "name": "Probabilistic cytoarchitectonic map of Area hOc3v (LingG)",
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+          "contentType": "application/octet-stream"
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+      ],
+      "contributors": [
+        "Rottschy, Claudia",
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Kujovic, Milenko",
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Eickhoff, Simon B."
+      ],
+      "kgReference": [
+        "10.25493/3K39-DNC"
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+        {
+          "name": "Ventral visual cortex in humans: Cytoarchitectonic mapping of two extrastriate areas",
+          "cite": "Rottschy, C., Eickhoff, S. B., Schleicher, A., Mohlberg, H., Kujovic, M., Zilles, K., & Amunts, K. (2007). Ventral visual cortex in humans: Cytoarchitectonic mapping of two extrastriate areas. Human Brain Mapping, 28(10), 1045–1059. ",
+          "doi": "10.1002/hbm.20348"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Caudal Middle Frontal and Rostral Middle Frontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
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+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_CMF-RMF_0"
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
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+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
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+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
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+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Pavone, Francesco S."
+      ],
+      "description": "This dataset contains images of neurofilament in human cortex obtained using serial two-photon microscopy. The individual 3D tiles acquired with the two-photon fluorescence microscope were fused together to produce the final image.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [
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+          "name": "Visual cortex area 17"
+        }
+      ],
+      "name": "Map of neurofilament in human brain cortex",
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+        "Pavone, Francesco S."
+      ],
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+        "10.25493/76F3-ZMZ"
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+      "formats": [
+        "NIFTI"
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+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Precentral and Supramarginal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_PrC-SM_0"
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+      ],
+      "name": "Probabilistic maps of lh_PrC-SM_0",
+      "files": [
+        {
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_PrC-SM_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Jankowsky, Joanna L."
+      ],
+      "description": "Bright-field microscopy images of serial coronal brain sections showing Pituitary homeobox 3 (Pitx3) promoter expression in a bigenic Pitx3-tetracycline-transactivator (tTA) mouse brain (case 3435, adult male), using a driver-reporter construct in which the Pitx3-tTA promoter regulates the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, which is visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Our data show that the Pitx3-tTA promoter is spatially restricted to the substantia nigra, ventral tegmental area, and a few other regions.",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Pituitary homeobox 3 tetracycline-transactivator expression: coronal sections (case 3435)",
+      "files": [],
+      "contributors": [
+        "Jankowsky, Joanna L.",
+        "Leergaard, Trygve B.",
+        "Puchades, Maja A.",
+        "Lillehaug, Sveinung",
+        "Bjaalie, Jan G.",
+        "Yetman, Michael J.",
+        "Checinska, Martyna M."
+      ],
+      "kgReference": [
+        "10.25493/FMGJ-4N3"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [
+        {
+          "name": "Allen adult mouse brain reference atlas V3"
+        }
+      ],
+      "custodians": [
+        "D'Angelo, Egidio"
+      ],
+      "description": "Study and characterization of the intrinsic excitability properties of different cerebellar neuronal types.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Recordings of cerebellar neuronal firing induced by currents steps",
+      "files": [],
+      "contributors": [
+        "Dieudonne, S.",
+        "Forti, L.",
+        "D'Angelo, Egidio",
+        "Isope, P.",
+        "Bidoret, C.",
+        "Pietrajtis, K.",
+        "Cesana, E."
+      ],
+      "kgReference": [
+        "10.25493/4AF6-WSD"
+      ],
+      "publications": [
+        {
+          "name": "Granule Cell Ascending Axon Excitatory Synapses onto Golgi Cells Implement a Potent Feedback Circuit in the Cerebellar Granular Layer",
+          "cite": "Cesana, E., Pietrajtis, K., Bidoret, C., Isope, P., D’Angelo, E., Dieudonne, S., & Forti, L. (2013). Granule Cell Ascending Axon Excitatory Synapses onto Golgi Cells Implement a Potent Feedback Circuit in the Cerebellar Granular Layer. Journal of Neuroscience, 33(30), 12430–12446. ",
+          "doi": "10.1523/JNEUROSCI.4897-11.2013"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Postcentral and Supramarginal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_PoC-SP_1"
+        }
+      ],
+      "name": "Probabilistic maps of rh_PoC-SP_1",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
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+          "name": "rh_PoC-SP_1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_PoC-SP_1.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Rostral Middle Frontal and Superior Frontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_RMF-SF_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_RMF-SF_0",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "lh_RMF-SF_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_RMF-SF_0.nii",
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area FG2 using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp, ar\n\nkainate (glutamate; [³H]kainate): fp, ar\n\nNMDA (glutamate; [³H]MK-801): fp, ar\n\nmGluR2/3 (glutamate; [³H] LY 341 495): ar\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp, ar\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp, ar\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp, ar\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp, ar\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp, ar\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp, ar\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp, ar\n\nα₁ (noradrenalin; [³H]prazosin): fp, ar\n\nα₂ (noradrenalin; [³H]UK-14,304): fp, ar\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp, ar\n\n5-HT₂ (serotonin; [³H]ketanserin): fp, ar\n\nD₁ (dopamine; [³H]SCH23390): fp, ar\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area FG2"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area FG2",
+      "files": [
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+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
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+          "name": "FG2_ar_examples.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_FG2/FG2_ar_examples.zip",
+          "contentType": "application/zip"
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+          "name": "FG2_fp_20180321.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_FG2/FG2_fp_20180321.xlsx",
+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Caspers, S.",
+        "Caspers, Julian",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike"
+      ],
+      "kgReference": [
+        "10.25493/VFCW-HXZ"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        },
+        {
+          "name": "Receptor architecture of visual areas in the face and word-form recognition region of the posterior fusiform gyrus",
+          "cite": "Caspers, J., Palomero-Gallagher, N., Caspers, S., Schleicher, A., Amunts, K., & Zilles, K. (2013). Receptor architecture of visual areas in the face and word-form recognition region of the posterior fusiform gyrus. Brain Structure and Function, 220(1), 205–219. ",
+          "doi": "10.1007/s00429-013-0646-z"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [],
+      "description": "Epidural EEG signal (16 recording electrodes) in response to electrical stimulation of left secondary motor cortex from head restrained rats, during wakefulness and during the exposure of low and high dosages of anesthetics (sevoflurane, propofol and ketamine). The electrical stimulation consists in about 100 single monophasic pulses of 1 ms, 50 uA, delivered at the rate of 0.1 Hz.\n\nThis dataset is temporarily under embargo. The data will become available for download after the embargo period.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Embargoed"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "PCI-like measure in rodents",
+      "files": [],
+      "contributors": [],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area FG1 (FusG) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area FG1 (FusG). The probability map of Area FG1 (FusG) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-FG1.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area FG1 (FusG)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area FG1 (FusG)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-FG1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-FG1.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
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+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Caspers, Julian",
+        "Amunts, Katrin",
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Eickhoff, Simon B.",
+        "Zilles, Karl"
+      ],
+      "kgReference": [
+        "10.25493/534D-V55"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonical analysis and probabilistic mapping of two extrastriate areas of the human posterior fusiform gyrus",
+          "cite": "Caspers, J., Zilles, K., Eickhoff, S. B., Schleicher, A., Mohlberg, H., & Amunts, K. (2012). Cytoarchitectonical analysis and probabilistic mapping of two extrastriate areas of the human posterior fusiform gyrus. Brain Structure and Function, 218(2), 511–526. ",
+          "doi": "10.1007/s00429-012-0411-8"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area TE 1.2 (HESCHL) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area TE 1.2 (HESCHL). The probability map of Area TE 1.2 (HESCHL) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-TE-12.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area TE 1.2 (HESCHL)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area TE 1.2 (HESCHL)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-TE-12.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-TE-12.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
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+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Rademacher, Jörg",
+        "Freund, H.-J.",
+        "Amunts, Katrin",
+        "Schormann, Thorsten",
+        "Werner, C.",
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Morosan, Patricia"
+      ],
+      "kgReference": [
+        "10.25493/T1WA-MBT"
+      ],
+      "publications": [
+        {
+          "name": "Human Primary Auditory Cortex: Cytoarchitectonic Subdivisions and Mapping into a Spatial Reference System",
+          "cite": "Morosan, P., Rademacher, J., Schleicher, A., Amunts, K., Schormann, T., & Zilles, K. (2001). Human Primary Auditory Cortex: Cytoarchitectonic Subdivisions and Mapping into a Spatial Reference System. NeuroImage, 13(4), 684–701. ",
+          "doi": "10.1006/nimg.2000.0715"
+        },
+        {
+          "name": "Probabilistic Mapping and Volume Measurement of Human Primary Auditory Cortex",
+          "cite": "Rademacher, J., Morosan, P., Schormann, T., Schleicher, A., Werner, C., Freund, H.-J., & Zilles, K. (2001). Probabilistic Mapping and Volume Measurement of Human Primary Auditory Cortex. NeuroImage, 13(4), 669–683. ",
+          "doi": "10.1006/nimg.2000.0714"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "Spike-time dependent plasticity (STDP is a particular form of Hebbian type of learning which consists in bidirectional modifications of synaptic strength according to the temporal order of pre- and postsynaptic spiking (*Dan Y1, Poo MM (2006) Spike timing-dependent plasticity: from synapse to perception. Physiol Rev 86:1033-1048*). Thus, positively correlated pre- and postsynaptic spiking (pre before post) within a critical window leads to long term potentiation (LTP), whereas a negative correlation (post before pre) leads to long term depression (LTD).  \nAt the neonatal stage, the hippocampal mossy fiber (MF)-CA3 is GABAergic and exhibits STDP. Our data demonstrate that, at the same age, positive pairing fails to induce STD-LTP at MF-CA3 synapses in hippocampal slices obtained from neuroligin-3 (NL3) knock-in (NL3<sup>R451C</sup>KI) and NL3 knock-out (KO) mice. Similarly, in NLR<sup>R451C</sup> KI mice, negative pairing failed to cause STD-LTD. In contrast, STD-LTP and STD-LTD can be readily produced in control age-matched WT littermates. In NLR<sup>R451C</sup> KI  mice, the impairment in STD-LTP is maintained in adulthood when MF are glutamatergic. This set of data refers to the neonate, C57BL/6 (wild-type), positive pairing condition. \n\n**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Embargoed"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Spike time dependent plasticity (STDP) data from neonate C57BL/6 (wild-type) mice, positive pairing",
+      "files": [],
+      "contributors": [
+        "Marchetti, Cristina",
+        "Cherubini, Enrico",
+        "Sgritta, Martina"
+      ],
+      "kgReference": [
+        "10.25493/NKRY-KA7"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "Spike-time dependent plasticity (STDP is a particular form of Hebbian type of learning which consists in bidirectional modifications of synaptic strength according to the temporal order of pre- and postsynaptic spiking (*Dan Y1, Poo MM (2006) Spike timing-dependent plasticity: from synapse to perception. Physiol Rev 86:1033-1048*). Thus, positively correlated pre- and postsynaptic spiking (pre before post) within a critical window leads to long term potentiation (LTP), whereas a negative correlation (post before pre) leads to long term depression (LTD).  \nAt the neonatal stage, the hippocampal mossy fiber (MF)-CA3 is GABAergic and exhibits STDP. Our data demonstrate that, at the same age, positive pairing fails to induce STD-LTP at MF-CA3 synapses in hippocampal slices obtained from neuroligin-3 (NL3) knock-in (NL3<sup>R451C</sup>KI) and NL3 knock-out (KO) mice. Similarly, in NLR<sup>R451C</sup> KI mice, negative pairing failed to cause STD-LTD. In contrast, STD-LTP and STD-LTD can be readily produced in control age-matched WT littermates. In NLR<sup>R451C</sup> KI  mice, the impairment in STD-LTP is maintained in adulthood when MF are glutamatergic. This set of data refers to the adult, C57BL/6 (wild-type), positive pairing condition. \n\n**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Spike time dependent plasticity (STDP) data from adult C57BL/6 (wild-type) mice, positive pairing",
+      "files": [],
+      "contributors": [
+        "Marchetti, Cristina",
+        "Sgritta, Martina",
+        "Cherubini, Enrico"
+      ],
+      "kgReference": [
+        "10.25493/K9VK-PPM"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Jankowsky, Joanna L."
+      ],
+      "description": "Bright-field microscopy images of serial horizontal brain sections showing Purkinje cell protein 2 (Pcp2) promoter expression in a bigenic Pcp2-tetracycline-transactivator (tTA) mouse brain (case 3292, adult female), generated using a driver-reporter construct in which the PCP2-tTA promoter regulates the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, which is visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Our data confirm earlier reports that Pcp2-tTA promoter expression is restricted to cerebellar Purkinje cells.",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Purkinje cell protein 2 tetracycline-transactivator expression: horizontal sections (case 3292)",
+      "files": [],
+      "contributors": [
+        "Jankowsky, Joanna L.",
+        "Checinska, Martyna M.",
+        "Yetman, Michael J.",
+        "Puchades, Maja A.",
+        "Lillehaug, Sveinung",
+        "Bjaalie, Jan G.",
+        "Leergaard, Trygve B."
+      ],
+      "kgReference": [
+        "10.25493/D1PR-55A"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area PFop (IPL) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area PFop (IPL). The probability map of Area PFop (IPL) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-PFop.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area PFop (IPL)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area PFop (IPL)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-PFop.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-PFop.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Schleicher, Axel",
+        "Geyer, Stefan",
+        "Caspers, S.",
+        "Zilles, Karl",
+        "Amunts, Katrin",
+        "Mohlberg, Hartmut",
+        "Eickhoff, Simon B.",
+        "Scheperjans, Filip"
+      ],
+      "kgReference": [
+        "10.25493/XYBW-69Q"
+      ],
+      "publications": [
+        {
+          "name": "The human inferior parietal lobule in stereotaxic space",
+          "cite": "Caspers, S., Eickhoff, S. B., Geyer, S., Scheperjans, F., Mohlberg, H., Zilles, K., & Amunts, K. (2008). The human inferior parietal lobule in stereotaxic space. Brain Structure and Function, 212(6), 481–495. ",
+          "doi": "10.1007/s00429-008-0195-z"
+        },
+        {
+          "name": "The human inferior parietal cortex: Cytoarchitectonic parcellation and interindividual variability",
+          "cite": "Caspers, S., Geyer, S., Schleicher, A., Mohlberg, H., Amunts, K., & Zilles, K. (2006). The human inferior parietal cortex: Cytoarchitectonic parcellation and interindividual variability. NeuroImage, 33(2), 430–448. ",
+          "doi": "10.1016/j.neuroimage.2006.06.054"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "electrophysiological data",
+        ".png",
+        ".mat"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Storm, Johan"
+      ],
+      "description": "Epidural EEG and hippocampal LFP signal in response to electrical stimulations of left secondary motor cortex from head restrained rats, during wakefulness and during the exposure of low dosages of anesthetics (sevoflurane). The electrical stimulations consist in monophasic pulses of 1 ms and multiple intesities (25, 50, 75, 100 uA; about 60 pulses for each intensity), delivered at the rate of 0.1 Hz.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial 4.0 International"
+      ],
+      "embargoStatus": [
+        "Embargoed"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Mechanistic analysis of ERP in rodents",
+      "files": [],
+      "contributors": [
+        "Alessandro, Arena"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Pars Opercularis and Precentral gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_Op-PrC_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_Op-PrC_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "lh_Op-PrC_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_Op-PrC_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area hOc1 using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp, pr, ar\n\nkainate (glutamate; [³H]kainate): fp, pr, ar\n\nNMDA (glutamate; [³H]MK-801): fp, pr, ar\n\nmGluR2/3 (glutamate; [³H] LY 341 495): pr, ar\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp, pr, ar\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp, pr, ar\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp, pr, ar\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp, pr, ar\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp, pr, ar\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp, pr, ar\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp, pr, ar\n\nα₁ (noradrenalin; [³H]prazosin): fp, pr, ar\n\nα₂ (noradrenalin; [³H]UK-14,304): fp, pr, ar\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp, pr, ar\n\n5-HT₂ (serotonin; [³H]ketanserin): fp, pr, ar\n\nD₁ (dopamine; [³H]SCH23390): fp, pr, ar\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area hOc1"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area hOc1",
+      "files": [
+        {
+          "byteSize": 1378323,
+          "name": "hOc1_ar_examples.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_hOc1/hOc1_ar_examples.zip",
+          "contentType": "application/zip"
+        },
+        {
+          "byteSize": 44096,
+          "name": "metadata.zip",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Mohlberg, Hartmut",
+        "Eickhoff, Simon B.",
+        "Amunts, Katrin",
+        "Scheperjans, Filip",
+        "Schleicher, Axel",
+        "Hoemke, L.",
+        "Zilles, Karl",
+        "Hermann, K."
+      ],
+      "kgReference": [
+        "10.25493/AHQS-ZR8"
+      ],
+      "publications": [
+        {
+          "name": "Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Hermann, K., Eickhoff, S. B., Amunts, K., Schleicher, A., & Zilles, K. (2007). Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex. Cerebral Cortex, 18(4), 846–867. ",
+          "doi": "10.1093/cercor/bhm116"
+        },
+        {
+          "name": "Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Eickhoff, S. B., Hoemke, L., Mohlberg, H., Hermann, K., Amunts, K., & Zilles, K. (2008). Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex. Cerebral Cortex, 18(9), 2141–2157. ",
+          "doi": "10.1093/cercor/bhm241"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area 6d1 (PreG) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area 6d1 (PreG). The probability map of Area 6d1 (PreG) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-6d1.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 6d1 (PreG)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area 6d1 (PreG)",
+      "files": [],
+      "contributors": [
+        "Sigl, Benjamin",
+        "Amunts, Katrin",
+        "Eickhoff, Simon B.",
+        "Mohlberg, Hartmut",
+        "Bludau, Sebastian",
+        "Caspers, Svenja"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Pars Opercularis and Precentral gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_Op-PrC_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_Op-PrC_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "rh_Op-PrC_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_Op-PrC_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area PFm using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp, pr, ar\n\nkainate (glutamate; [³H]kainate): fp, pr, ar\n\nNMDA (glutamate; [³H]MK-801): fp, pr, ar\n\nmGluR2/3 (glutamate; [³H] LY 341 495): pr, ar\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp, pr, ar\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp, pr, ar\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp, pr, ar\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp, pr, ar\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp, pr, ar\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp, pr, ar\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp, pr, ar\n\nα₁ (noradrenalin; [³H]prazosin): fp, pr, ar\n\nα₂ (noradrenalin; [³H]UK-14,304): fp, pr, ar\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp, pr, ar\n\n5-HT₂ (serotonin; [³H]ketanserin): fp, pr, ar\n\nD₁ (dopamine; [³H]SCH23390): fp, pr, ar\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area PFm"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area PFm",
+      "files": [
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+          "byteSize": 1087485,
+          "name": "PFm_ar_examples.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_PFm/PFm_ar_examples.zip",
+          "contentType": "application/zip"
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+          "byteSize": 16170,
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_PFm/PFm_fp_20171202.xlsx",
+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        },
+        {
+          "byteSize": 601622,
+          "name": "PFm_pr_examples.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_PFm/PFm_pr_examples.zip",
+          "contentType": "application/zip"
+        },
+        {
+          "byteSize": 44096,
+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Caspers, S.",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike"
+      ],
+      "kgReference": [
+        "10.25493/FS3T-2R8"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        },
+        {
+          "name": "Organization of the Human Inferior Parietal Lobule Based on Receptor Architectonics",
+          "cite": "Caspers, S., Schleicher, A., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Zilles, K. (2012). Organization of the Human Inferior Parietal Lobule Based on Receptor Architectonics. Cerebral Cortex, 23(3), 615–628. ",
+          "doi": "10.1093/cercor/bhs048"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area 44v using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp\n\nkainate (glutamate; [³H]kainate): fp\n\nNMDA (glutamate; [³H]MK-801): fp\n\nmGluR2/3 (glutamate; [³H] LY 341 495): fp\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp\n\nα₁ (noradrenalin; [³H]prazosin): fp\n\nα₂ (noradrenalin; [³H]UK-14,304): fp\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp\n\n5-HT₂ (serotonin; [³H]ketanserin): fp\n\nD₁ (dopamine; [³H]SCH23390): fp\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 44v"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area 44v",
+      "files": [
+        {
+          "byteSize": 44096,
+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        },
+        {
+          "byteSize": 16337,
+          "name": "44v_fp_20180405.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_44v/44v_fp_20180405.xlsx",
+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        }
+      ],
+      "contributors": [
+        "Friederici, Angela D.",
+        "Morosan, Patricia",
+        "Schleicher, Axel",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike",
+        "Zilles, Karl"
+      ],
+      "kgReference": [
+        "10.25493/P82M-PVM"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        },
+        {
+          "name": "Broca's Region: Novel Organizational Principles and Multiple Receptor Mapping",
+          "cite": "Amunts, K., Lenzen, M., Friederici, A. D., Schleicher, A., Morosan, P., Palomero-Gallagher, N., & Zilles, K. (2010). Broca’s Region: Novel Organizational Principles and Multiple Receptor Mapping. PLoS Biology, 8(9), e1000489. ",
+          "doi": "10.1371/journal.pbio.1000489"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Lateral Orbitofrontal and Rostral Middle Frontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_LOF-RMF_1"
+        }
+      ],
+      "name": "Probabilistic maps of lh_LOF-RMF_1",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "lh_LOF-RMF_1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_LOF-RMF_1.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [],
+      "description": null,
+      "licenseInfo": [],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "",
+      "files": [],
+      "contributors": [],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [
+        {
+          "name": "Allen adult mouse brain reference atlas V2"
+        }
+      ],
+      "custodians": [
+        "Jankowsky, Joanna L."
+      ],
+      "description": "Bright-field microscopy images of serial coronal brain sections showing neuropsin (Nop) promoter expression in a bigenic Nop-tetracycline-transactivator (tTA) mouse brain, (case 2849 adult female), using a driver-reporter construct in which the Nop-tTA promoter regulates the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, which is visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Methodological details are provided in Yetman et al., Brain Struct Funct 221:2231-49, 2016. Our data show that the Nop-tTA promoter mainly is expressed in the entorhinal cortex, but also in several other cortical regions.",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Neuropsin tetracycline-transactivator expression: coronal sections (case 2849)",
+      "files": [],
+      "contributors": [
+        "Lillehaug, Sveinung",
+        "Bjaalie, Jan G.",
+        "Yetman, Michael J.",
+        "Jankowsky, Joanna L.",
+        "Leergaard, Trygve B."
+      ],
+      "kgReference": [
+        "10.25493/WB6K-V72"
+      ],
+      "publications": [
+        {
+          "name": "Transgene expression in the Nop-tTA driver line is not inherently restricted to the entorhinal cortex",
+          "cite": "Yetman, M. J., Lillehaug, S., Bjaalie, J. G., Leergaard, T. B., & Jankowsky, J. L. (2015). Transgene expression in the Nop-tTA driver line is not inherently restricted to the entorhinal cortex. Brain Structure and Function, 221(4), 2231–2249. ",
+          "doi": "10.1007/s00429-015-1040-9"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "DeFelipe, Javier"
+      ],
+      "description": "This dataset contains the density of VGAT-ir Complex basket formations (Cbk-formations) in various cytoarchitectonic areas of the human cerebral cortex. Cell density was analyzed on cell-body-stained histological sections of 5 human postmortem brains that were supplied by Dr R. Alcaraz, Forensic Pathology Service, Basque Institute of Legal Medicine, Bilbao, Spain.",
+      "licenseInfo": [],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Brodmann’s area 3b"
+        },
+        {
+          "name": "Brodmann’s area 32"
+        },
+        {
+          "name": "Brodmann’s area 24"
+        },
+        {
+          "name": "Brodmann’s area 38"
+        },
+        {
+          "name": "Brodmann’s area 22"
+        },
+        {
+          "name": "Brodmann’s area 21"
+        },
+        {
+          "name": "Brodmann’s area 20"
+        },
+        {
+          "name": "Brodmann’s area 47"
+        },
+        {
+          "name": "Brodmann’s area 14"
+        },
+        {
+          "name": "Brodmann’s area 13"
+        },
+        {
+          "name": "Brodmann’s area 12"
+        },
+        {
+          "name": "Brodmann’s area 11"
+        },
+        {
+          "name": "Brodmann’s area 46"
+        },
+        {
+          "name": "Brodmann’s area 45"
+        },
+        {
+          "name": "Brodmann’s area 10"
+        },
+        {
+          "name": "Brodmann’s area 9"
+        },
+        {
+          "name": "Brodmann’s area 4"
+        },
+        {
+          "name": "Brodmann’s area 18"
+        },
+        {
+          "name": "Brodmann’s area 17"
+        }
+      ],
+      "name": "Distribution and density of Complex basket formations in the human cerebral cortex",
+      "files": [],
+      "contributors": [
+        "Blazquez-Llorca, Lidia",
+        "DeFelipe, Javier",
+        "García-Marín, Virginia"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "GABAergic complex basket formations in the human neocortex",
+          "cite": "Blazquez-Llorca, L., García-Marín, V., & DeFelipe, J. (2010). GABAergic complex basket formations in the human neocortex. The Journal of Comparative Neurology, 518(24), 4917–4937. ",
+          "doi": "10.1002/cne.22496"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area TE 3 (STG) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area TE 3 (STG). The probability map of Area TE 3 (STG) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-TE-3.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area TE 3 (STG)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area TE 3 (STG)",
+      "files": [
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+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
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+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-TE-3.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-TE-3.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Morosan, Patricia",
+        "Schleicher, Axel",
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Geyer, Stefan"
+      ],
+      "kgReference": [
+        "10.25493/V09X-3EW"
+      ],
+      "publications": [
+        {
+          "name": "Multimodal architectonic mapping of human superior temporal gyrus",
+          "cite": "Morosan, P., Schleicher, A., Amunts, K., & Zilles, K. (2005). Multimodal architectonic mapping of human superior temporal gyrus. Anatomy and Embryology, 210(5-6), 401–406. ",
+          "doi": "10.1007/s00429-005-0029-1"
+        },
+        {
+          "name": "Observer-Independent Method for Microstructural Parcellation of Cerebral Cortex: A Quantitative Approach to Cytoarchitectonics",
+          "cite": "Schleicher, A., Amunts, K., Geyer, S., Morosan, P., & Zilles, K. (1999). Observer-Independent Method for Microstructural Parcellation of Cerebral Cortex: A Quantitative Approach to Cytoarchitectonics. NeuroImage, 9(1), 165–177. ",
+          "doi": "10.1006/nimg.1998.0385"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Riess, Olaf"
+      ],
+      "description": "Bright-field microscopy images of serial coronal brain sections showing prion promoter (Prnp) promoter expression in a bigenic Prnp-tetracycline-transactivator (tTA) mouse brain (case 388.12, adult female), using a driver-reporter construct in which the Prnp-tTA promoter regulates the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, which is visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Methodological details are provided in Boy et al., Neuroimage 33:449-62, 2006. Our data show that the Prnp-tTA promoter is spatially expressed in multiple brain regions, including the cerebral cortex, several basal ganglia regions, hippocampus, tectum, and cerebellum.",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Prion promoter tetracycline-transactivator expression: coronal sections (case 388.12)",
+      "files": [],
+      "contributors": [
+        "Riess, Olaf",
+        "Holzmann, Carsten",
+        "Odeh, Francis",
+        "Nuber, Silke",
+        "Wree, Andreas",
+        "Leergaard, Trygve B.",
+        "Bjaalie, Jan G.",
+        "Bichelmeier, Ulrike",
+        "Boy, Jana",
+        "Bujard, Hermann",
+        "Prusiner, Stanley B.",
+        "Schmidt, Thorsten"
+      ],
+      "kgReference": [
+        "10.25493/T9P1-WH4"
+      ],
+      "publications": [
+        {
+          "name": "Expression mapping of tetracycline-responsive prion protein promoter: Digital atlasing for generating cell-specific disease models",
+          "cite": "Boy, J., Leergaard, T. B., Schmidt, T., Odeh, F., Bichelmeier, U., Nuber, S., … Bjaalie, J. G. (2006). Expression mapping of tetracycline-responsive prion protein promoter: Digital atlasing for generating cell-specific disease models. NeuroImage, 33(2), 449–462. ",
+          "doi": "10.1016/j.neuroimage.2006.05.055"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Danbolt,  Niels C."
+      ],
+      "description": "Glutamate is the major excitatory transmitter in the central nervous system (Danbolt, Prog. Neurobiol. 65:1-105, 2001). It is inactivated by cellular uptake, mostly catalyzed by the glutamate transporters GLT1 (slc1a2, excitatory amino acid transporter [EAAT2]) subtype expressed at high levels in brain astrocytes and at lower levels in neurons. Three C-terminal variants of EAAT2 exist: GLT1a (Pines et al., Nature 360:464-467, 1992), GLT1b (Utsunomiya-Tate et al., FEBS Lett 416:312-326,1997), and GLT1c (Rauen et al., Neurochem. Int. 45:1095-1106, 2004). This dataset is brain-wide collection of microscopic images showing the brain-wide distribution of GLT1 in the mouse and rat brain, visualized by immunohistochemistry using antibodies against GLT1a and GLT1b. To facilitate identification of anatomical location adjacent section were stained to reveal cyto- and myeloarchitecture.",
+      "licenseInfo": [
+        "Creative Commons Attribution-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Brain-wide distribution of glutamate type 1 transporter protein (GLT1)",
+      "files": [],
+      "contributors": [
+        "Holmseth, Silvia",
+        "Danbolt, Nils C.",
+        "Bjaalie, Jan G.",
+        "Leergaard, Trygve B.",
+        "Lehre, K.P.",
+        "Real, Katia",
+        "Scott, Heather A."
+      ],
+      "kgReference": [
+        "10.25493/Y147-2CE"
+      ],
+      "publications": [
+        {
+          "name": "The concentrations and distributions of three C-terminal variants of the GLT1 (EAAT2; slc1a2) glutamate transporter protein in rat brain tissue suggest differential regulation",
+          "cite": "Holmseth, S., Scott, H. A., Real, K., Lehre, K. P., Leergaard, T. B., Bjaalie, J. G., & Danbolt, N. C. (2009). The concentrations and distributions of three C-terminal variants of the GLT1 (EAAT2; slc1a2) glutamate transporter protein in rat brain tissue suggest differential regulation. Neuroscience, 162(4), 1055–1071. ",
+          "doi": "10.1016/j.neuroscience.2009.03.048"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "Nifti Files, gifti files, csv files, json files"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Thirion, Bertrand"
+      ],
+      "description": "This dataset contains functional magnetic resonance images (fMRIs) of 12 subjects performing HCP Emotional task aiming to capture neural activity related to the perception of fear and anger. Affective facial expressions were used as visual stimuli due to their importance in adaptive social behavior. The paradigm included two categories of blocks, namely face and shape blocks. All blocks consisted of a series of events, in which images of faces or shapes were displayed, respectively. There were always three faces/shapes per image; one face/shape was shown at the top and two faces/shapes were shown at the bottom. The participants were then asked to decide which face/shape at the bottom, i.e. left or right face/shape, matched the one displayed at the top, by pressing the corresponding button of the response box. The task was formed by twelve blocks per run, i.e. six face blocks and six shape blocks. The two block categories were alternately presented for each run. All blocks contained six trials and they were always initiated by a cue of three seconds. In turn, the trials included a visual-stimulus period of two seconds and a fixation-cross period of one second; the total duration of the trial was thus three seconds.\n\n[https://openfmri.org/dataset/ds000244/](https://openfmri.org/dataset/ds000244/)\n\n[https://neurovault.org/collections/2138/](https://neurovault.org/collections/2138/)",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Individual Brain Charting: HCP Emotion",
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+      "description": "This dataset contains the distinct architectonic Area 33 (ACC) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Area 33 (ACC). The probability map of Area 33 (ACC) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-33.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 33 (ACC)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area 33 (ACC)",
+      "files": [
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
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+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-33.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-33.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Mohlberg, Hartmut",
+        "Zilles, Karl",
+        "Amunts, Katrin",
+        "Vogt, Brent A.",
+        "Schleicher, Axel",
+        "Hoffstaedter, Felix",
+        "Eickhoff, Simon B.",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "kgReference": [
+        "10.25493/S6PK-Z7E"
+      ],
+      "publications": [
+        {
+          "name": "Functional organization of human subgenual cortical areas: Relationship between architectonical segregation and connectional heterogeneity",
+          "cite": "Palomero-Gallagher, N., Eickhoff, S. B., Hoffstaedter, F., Schleicher, A., Mohlberg, H., Vogt, B. A., … Zilles, K. (2015). Functional organization of human subgenual cortical areas: Relationship between architectonical segregation and connectional heterogeneity. NeuroImage, 115, 177–190. ",
+          "doi": "10.1016/j.neuroimage.2015.04.053"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area Id7 (Insular dysgranular area 7) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains, obtained from the body donor program of the University of Düsseldorf. Subsequently, the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain, where each voxel is assigned with the probability to belong to Area Id7 (Insula). The probability map of Area Id7 (Insula) in right and left hemisphere is given in files jubrain-pmap-v22c_space-mnicolin27_Area-Id7.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets. ",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area Id7 (Insula)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area Id7 (Insula)",
+      "files": [],
+      "contributors": [
+        "Amunts, Katrin",
+        "Adalat, Reza",
+        "Mohlberg, Hartmut",
+        "Bludau, Sebastian",
+        "Iannilli, Francesca"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area ifs1 (IFS) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area ifs1 (IFS). The probability map of  Area ifs1 (IFS) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-ifs1.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area ifs1 (IFS)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area ifs1 (IFS)",
+      "files": [],
+      "contributors": [
+        "Bradler, Sabine",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [
+        {
+          "name": "Allen adult mouse brain reference atlas V3"
+        }
+      ],
+      "custodians": [
+        "D'Angelo, Egidio"
+      ],
+      "description": "Study and characterization of the intrinsic properties of granule cells.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Recordings of cerebellar granule cells current-voltage relations",
+      "files": [],
+      "contributors": [
+        "D'Angelo, Egidio",
+        "Tognolina, Marialuisa"
+      ],
+      "kgReference": [
+        "10.25493/MDAR-XEB"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area PGp using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp\n\nkainate (glutamate; [³H]kainate): fp\n\nNMDA (glutamate; [³H]MK-801): fp\n\nmGluR2/3 (glutamate; [³H] LY 341 495): fp\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp\n\nα₁ (noradrenalin; [³H]prazosin): fp\n\nα₂ (noradrenalin; [³H]UK-14,304): fp\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp\n\n5-HT₂ (serotonin; [³H]ketanserin): fp\n\nD₁ (dopamine; [³H]SCH23390): fp\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area PGp"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area PGp",
+      "files": [
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+          "byteSize": 16278,
+          "name": "PGp_fp_20180405.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_PGp/PGp_fp_20180405.xlsx",
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+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Caspers, S.",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike"
+      ],
+      "kgReference": [
+        "10.5072/AW9Y-VEU"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        },
+        {
+          "name": "Organization of the Human Inferior Parietal Lobule Based on Receptor Architectonics",
+          "cite": "Caspers, S., Schleicher, A., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Zilles, K. (2012). Organization of the Human Inferior Parietal Lobule Based on Receptor Architectonics. Cerebral Cortex, 23(3), 615–628. ",
+          "doi": "10.1093/cercor/bhs048"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Caudal Middle Frontal and Precentral gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_CMF-PrC_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_CMF-PrC_0",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "rh_CMF-PrC_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_CMF-PrC_0.nii",
+          "contentType": "application/octet-stream"
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+        {
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+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Posterior Cingulate and Precuneus gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_PoCi-PrCu_2"
+        }
+      ],
+      "name": "Probabilistic maps of rh_PoCi-PrCu_2",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "rh_PoCi-PrCu_2.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_PoCi-PrCu_2.nii",
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "Nifti Files, gifti files, csv files, json files"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Thirion, Bertrand"
+      ],
+      "description": "This dataset contains functional magnetic resonance images (fMRIs) of 12 subjects performing a variety of elementary cognitive functions, ranging from perceptual processing to high-cognition. The task was organized as a fast event-related paradigm, composed of trials of ten different conditions: (1) left-hand three-times button press, indicated by visual instruction; (2) right-hand three-times button press, indicated by visual instruction; (3) left-hand three-times button press, indicated by auditory instruction; (4) right-hand three-times button press, indicated by auditory instruction; (5) listen to narrative sentences; (6) read narrative sentences; (7) viewing of flashing horizontal checkerboards; (8) viewing of flashing vertical checkerboards; (9) silent subtraction, indicated by visual instruction; and (10) silent subtraction, indicated by auditory instruction. The task comprised eighty trials in one single run. There were two runs within the same session, in which two different sequences of trials were presented. The sequence of trials per run was pseudo-randomized for the session, but fixed for all participants. The duration of the trials ranged between two and four seconds. There were twenty two epochs of rest between trials, in which a fixation cross was displayed.\n\n[https://openfmri.org/dataset/ds000244/](https://openfmri.org/dataset/ds000244/)\n\n[https://neurovault.org/collections/2138/](https://neurovault.org/collections/2138/)",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Individual Brain Charting: ARCHI standard",
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+        "Varoquaux, Gaël",
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+        "Pinel, Philippe",
+        "Martins, Bernadette",
+        "Doublé, Christine",
+        "Médiouni-Cloarec, Gaëlle",
+        "Joly-Testault, Véronique",
+        "Laurier, Laurence",
+        "Roger, Séverine",
+        "Becuwe-Desmidt, Séverine",
+        "Ginisty, Chantal",
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+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
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+        "Benavides-Piccione, Ruth",
+        "Leon, Gonzalo",
+        "Regalado, Mamen",
+        "Cano, Deborah",
+        "Gonzalez-Tapia, Silvia",
+        "DeFelipe, Javier",
+        "Kastanauskaite, Asta",
+        "Rojo, Concepcion."
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+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
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+        "Mohlberg, Hartmut",
+        "Amunts, Katrin",
+        "Minnerop, Martina",
+        "Eickhoff, Simon B.",
+        "Bludau, Sebastian",
+        "Tellmann, Stefanie"
+      ],
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+          "cite": "Tellmann, S., Bludau, S., Eickhoff, S., Mohlberg, H., Minnerop, M., & Amunts, K. (2015). Cytoarchitectonic mapping of the human brain cerebellar nuclei in stereotaxic space and delineation of their co-activation patterns. Frontiers in Neuroanatomy, 09. ",
+          "doi": "10.3389/fnana.2015.00054"
+        }
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+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
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+      "custodians": [
+        "Genon, Sarah"
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+      "description": "Five functional subregions have been defined in the right dorsal premotor cortex by computing meta-analytic connectivity modeling (MACM) in the BrainMap database.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
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+          "name": "Central subregion of right dorsal premotor cortex"
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+          "name": "Caudal subregion of right dorsal premotor cortex"
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+          "name": "CentralRightPMd_C3.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000773/RightPMdParcels/CentralRightPMd_C3.nii",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000773/RightPMdParcels/CaudalRightPMd_C2.nii",
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+          "name": "DorsalRightPMd_C5.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000773/RightPMdParcels/DorsalRightPMd_C5.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Genon, Sarah",
+        "Eickhoff, Simon B.",
+        "Jiang, Tianzi",
+        "Amunts, Katrin",
+        "Caspers, S.",
+        "Moebus, Susanne",
+        "Fox, P.T.",
+        "Grefkes, Christian",
+        "Langner, Robert",
+        "Reid, Andrew T.",
+        "Hoffstaedter, Felix",
+        "Cieslik, Edna C.",
+        "Müller, Veronika I.",
+        "Fan, Lingzhong",
+        "Li, Hai"
+      ],
+      "kgReference": [
+        "10.25493/3MA9-GYF"
+      ],
+      "publications": [
+        {
+          "name": "The Right Dorsal Premotor Mosaic: Organization, Functions, and Connectivity",
+          "cite": "Genon, S., Li, H., Fan, L., Müller, V. I., Cieslik, E. C., Hoffstaedter, F., … Eickhoff, S. B. (2016). The Right Dorsal Premotor Mosaic: Organization, Functions, and Connectivity. Cerebral Cortex, bhw065. ",
+          "doi": "10.1093/cercor/bhw065"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "DeFelipe, Javier"
+      ],
+      "description": "We have processed brain material from transgenic mice expressing the enhanced green fluorescent protein (EGFP) coupled with the synaptic protein PSD95 (EGFP95) in order to accomplish the automated counting process using 3D connected components of fluorescent puncta in stacks of confocal microscope images for the CA1 region of the hippocampal formation. Furthermore, we have developed a PSDs volume segmentation and quantification algorithm designed to be executed in a supercomputer in order to obtain results in multiple brain regions in a short time. We have currently uploaded 6 examples of the 3D automated counting process of the PSD95 protein using confocal microscopy, from the following CA1 regions: stratum oriens (SO), CA1 stratum radiatum (SR), CA1 stratum lacunosum moleculare (SLM).\\r\\nIn addition, brain sections in the same regions and layers as those proccesed for confocal microscopy, have been processed for 3D electron microscopy using FIB/SEM in order to crossvalidate and interpret confocal data with ultrastructural data with on the number and size of PSD puncta in different brain regions. We have currently uploaded 1 example of the 3D counting process of PSD puncta using FIB/SEM from the CA1 SR region.\n\n**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Synapse maps - confocal",
+      "files": [],
+      "contributors": [
+        "Gonzalez, Santiago",
+        "Kastanauskaite, Asta",
+        "Alvarez, Carmen",
+        "Benevides, Ruth",
+        "Rodriguez, Rodrigo",
+        "Valdes, Lorena",
+        "DeFelipe, Javier",
+        "Muñoz, A",
+        "Tapia, Silvia",
+        "Merchan-Perez, Angel",
+        "Santuy, Andrea"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area FG2 (FusG) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area FG2 (FusG). The probability map of Area FG2 (FusG) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-FG2.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area FG2 (FusG)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area FG2 (FusG)",
+      "files": [
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-FG2.nii",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Caspers, Julian",
+        "Amunts, Katrin",
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Eickhoff, Simon B.",
+        "Zilles, Karl"
+      ],
+      "kgReference": [
+        "10.25493/X835-SK7"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonical analysis and probabilistic mapping of two extrastriate areas of the human posterior fusiform gyrus",
+          "cite": "Caspers, J., Zilles, K., Eickhoff, S. B., Schleicher, A., Mohlberg, H., & Amunts, K. (2012). Cytoarchitectonical analysis and probabilistic mapping of two extrastriate areas of the human posterior fusiform gyrus. Brain Structure and Function, 218(2), 511–526. ",
+          "doi": "10.1007/s00429-012-0411-8"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic CA3 (Hippocampus) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to CA3 (Hippocampus). The probability map of CA3 (Hippocampus) is given in file jubrain-pmap-v22c_space-mnicolin27_Hippocampus-CA3.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "CA3 (Hippocampus)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of CA3 (Hippocampus)",
+      "files": [
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+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Hippocampus-CA3.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Habel, U.",
+        "Zilles, Karl",
+        "Schneider, F.",
+        "Shah, Nadim J.",
+        "Mohlberg, Hartmut",
+        "Pieperhoff, P.",
+        "Kindler, M.",
+        "Kedo, O.",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [
+        "10.25493/CQSD-FDR"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps",
+          "cite": "Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N. J., … Zilles, K. (2005). Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and Embryology, 210(5-6), 343–352. ",
+          "doi": "10.1007/s00429-005-0025-5"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Interposed Nucleus (Cerebellum) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Interposed Nucleus (Cerebellum). The probability map of Interposed Nucleus (Cerebellum) is given in file jubrain-pmap-v22c_space-mnicolin27_Cerebellum-Ninterp.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Interposed Nucleus (Cerebellum)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Interposed Nucleus (Cerebellum)",
+      "files": [
+        {
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+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
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+          "name": "jubrain-pmap-v22c_space-mnicolin27_Cerebellum-Ninterp.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Cerebellum-Ninterp.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Mohlberg, Hartmut",
+        "Amunts, Katrin",
+        "Minnerop, Martina",
+        "Eickhoff, Simon B.",
+        "Bludau, Sebastian",
+        "Tellmann, Stefanie"
+      ],
+      "kgReference": [
+        "10.25493/8MRR-JHC"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonic mapping of the human brain cerebellar nuclei in stereotaxic space and delineation of their co-activation patterns",
+          "cite": "Tellmann, S., Bludau, S., Eickhoff, S., Mohlberg, H., Minnerop, M., & Amunts, K. (2015). Cytoarchitectonic mapping of the human brain cerebellar nuclei in stereotaxic space and delineation of their co-activation patterns. Frontiers in Neuroanatomy, 09. ",
+          "doi": "10.3389/fnana.2015.00054"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Supramarginal and Insula gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_SM-Ins_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_SM-Ins_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
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+        {
+          "byteSize": 68240520,
+          "name": "rh_SM-Ins_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_SM-Ins_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area 45 using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp, pr, ar\n\nkainate (glutamate; [³H]kainate): fp, pr, ar\n\nNMDA (glutamate; [³H]MK-801): fp, pr, ar\n\nmGluR2/3 (glutamate; [³H] LY 341 495): pr, ar\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp, pr, ar\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp, pr, ar\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp, pr, ar\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp, pr, ar\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp, pr, ar\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp, pr, ar\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp, pr, ar\n\nα₁ (noradrenalin; [³H]prazosin): fp, pr, ar\n\nα₂ (noradrenalin; [³H]UK-14,304): fp, pr, ar\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp, pr, ar\n\n5-HT₂ (serotonin; [³H]ketanserin): fp, pr, ar\n\nD₁ (dopamine; [³H]SCH23390): fp, pr, ar\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 45"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area 45",
+      "files": [
+        {
+          "byteSize": 16165,
+          "name": "45_fp_20171202.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_45/45_fp_20171202.xlsx",
+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        },
+        {
+          "byteSize": 44096,
+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        },
+        {
+          "byteSize": 407104,
+          "name": "45_pr_examples.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_45/45_pr_examples.zip",
+          "contentType": "application/zip"
+        },
+        {
+          "byteSize": 972972,
+          "name": "45_ar_examples.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_45/45_ar_examples.zip",
+          "contentType": "application/zip"
+        }
+      ],
+      "contributors": [
+        "Friederici, Angela D.",
+        "Morosan, Patricia",
+        "Schleicher, Axel",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike",
+        "Zilles, Karl"
+      ],
+      "kgReference": [
+        "10.25493/QFSY-YWC"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        },
+        {
+          "name": "Broca's Region: Novel Organizational Principles and Multiple Receptor Mapping",
+          "cite": "Amunts, K., Lenzen, M., Friederici, A. D., Schleicher, A., Morosan, P., Palomero-Gallagher, N., & Zilles, K. (2010). Broca’s Region: Novel Organizational Principles and Multiple Receptor Mapping. PLoS Biology, 8(9), e1000489. ",
+          "doi": "10.1371/journal.pbio.1000489"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area hOc2 (V2, 18) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area hOc2 (V2, 18). The probability map of  Area hOc2 (V2, 18) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-hOc2.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area hOc2 (V2, 18)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area hOc2 (V2, 18)",
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+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Schormann, Thorsten",
+        "Mohlberg, Hartmut",
+        "Malikovic, Aleksandar"
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+        "10.25493/FKMC-ZX7"
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+          "cite": "Amunts, K., Malikovic, A., Mohlberg, H., Schormann, T., & Zilles, K. (2000). Brodmann’s Areas 17 and 18 Brought into Stereotaxic Space—Where and How Variable? NeuroImage, 11(1), 66–84. ",
+          "doi": "10.1006/nimg.1999.0516"
+        }
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+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
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+        "Free"
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+      "parcellationRegion": [
+        {
+          "name": "Area hOc4la (LOC)"
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+      ],
+      "contributors": [
+        "Malikovic, Aleksandar",
+        "Zilles, Karl",
+        "Eickhoff, Simon B.",
+        "Palomero-Gallagher, Nicola",
+        "Kujovic, Milenko",
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Amunts, Katrin"
+      ],
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+        "10.25493/FCQW-EZU"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitecture of the human lateral occipital cortex: mapping of two extrastriate areas hOc4la and hOc4lp",
+          "cite": "Malikovic, A., Amunts, K., Schleicher, A., Mohlberg, H., Kujovic, M., Palomero-Gallagher, N., … Zilles, K. (2015). Cytoarchitecture of the human lateral occipital cortex: mapping of two extrastriate areas hOc4la and hOc4lp. Brain Structure and Function, 221(4), 1877–1897. ",
+          "doi": "10.1007/s00429-015-1009-8"
+        }
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+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
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+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
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+          "doi": "10.1016/j.neuroimage.2016.11.066"
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+        "Poupon, Cyril"
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+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Middle Orbitofrontal and Superior Temporal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
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+          "name": "lh_MOF-ST_0"
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+        "Mangin, Jean-François",
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+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
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+      "parcellationRegion": [],
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+        "Pinho, Ana Luísa",
+        "Thirion, Bertrand",
+        "Hertz-Pannier, Lucie",
+        "Dehaene, Stanislas",
+        "Pallier, Christophe",
+        "Varoquaux, Gaël",
+        "Eger, Evelyn",
+        "Pinel, Philippe",
+        "Martins, Bernadette",
+        "Doublé, Christine",
+        "Médiouni-Cloarec, Gaëlle",
+        "Joly-Testault, Véronique",
+        "Laurier, Laurence",
+        "Roger, Séverine",
+        "Becuwe-Desmidt, Séverine",
+        "Ginisty, Chantal",
+        "Denghien, Isabelle",
+        "Dohmatob, Elvis",
+        "Fabre, Murielle",
+        "Ruest, Torsten",
+        "Amadon, Alexis"
+      ],
+      "kgReference": [
+        "10.25493/PR7B-HND"
+      ],
+      "publications": [
+        {
+          "name": "Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping",
+          "cite": "Pinho, A. L., Amadon, A., Ruest, T., Fabre, M., Dohmatob, E., Denghien, I., … Thirion, B. (2018). Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping. Scientific Data, 5, 180105. ",
+          "doi": "10.1038/sdata.2018.105"
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+      "custodians": [
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+      "description": "This dataset contains the distinct architectonic Area Id1 (Insula) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Area Id1 (Insula). The probability map of Area Id1 (Insula) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-Id1.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
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+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area Id1 (Insula)"
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-Id1.nii",
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+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Kurth, F.",
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Hoemke, L.",
+        "Schleicher, Axel",
+        "Eickhoff, Simon B."
+      ],
+      "kgReference": [
+        "10.25493/KPB6-2AX"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitecture and Probabilistic Maps of the Human Posterior Insular Cortex",
+          "cite": "Kurth, F., Eickhoff, S. B., Schleicher, A., Hoemke, L., Zilles, K., & Amunts, K. (2009). Cytoarchitecture and Probabilistic Maps of the Human Posterior Insular Cortex. Cerebral Cortex, 20(6), 1448–1461. ",
+          "doi": "10.1093/cercor/bhp208"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "Nifti, Csv, Txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Thirion, Bertrand"
+      ],
+      "description": "#TitleARCHI fMRI Database: social paradigm##SummaryThis dataset contains functional magnetic resonance images (fMRIs) of 77 subjects performing different tasks of a  social paradigm: 1) speech versus non-speech sounds, 2) false belief- versus mechanistic kind of inference after visual or auditory presentation, 3) interacting versus non-interacting figures in the movie clip. The tasks were executed in a (small) block design (5-7s each) with acquisition duration of  489s.\nVisual stimuli were displayed in four 250-ms epochs, separated by 100ms intervals (i.e., 1.3s in total). Auditory stimuli were drawn from a recorded male voice (i.e., a total of 1.6s for motor instructions, 1.2-1.7s for sentences, and 1.2-1.3s for subtraction). The auditory or visual stimuli were shown to the participants for passive viewing or button response in event-related paradigms. Post-scan questions verified that the experimental tasks were understood and followed correctly. \nWhole-brain EPI data were acquired with the same Siemens Trio with a 32 channel head coil (TR=2400ms, TE=30ms, flip angle=60°, in-plane FOV= 19.2 * 19.2 cm, 40 slices, 3.0mm isotropic voxels). A posterior-anterior phase encoding scheme was used for all images. Standard preprocessing was performed with SPM, including slice timing, motion correction, alignment, and spatial normalization.",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "ARCHI_fMRI",
+      "files": [],
+      "contributors": [
+        "Yeh, Chun-Hung",
+        "Lebois, Alice",
+        "Poupon, Fabrice",
+        "Rivière, Denis",
+        "Roca, Pauline",
+        "Duclap, Delphine",
+        "Thirion, Bertrand",
+        "Poupon, Cyril",
+        "Pinel, Philippe"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "This study aimed to address the functional role of transynaptic signaling in the formation, stabilization and plasticity of the synapses and lastly, to generate modeling data.   \n**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Short-term plasticity (STP) at GABAergic synapses",
+      "files": [],
+      "contributors": [
+        "Pizzarelli, Rocco",
+        "Giustizieri, Michela",
+        "Marinelli, Silvia",
+        "Pimpinella, Domenico"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area 7A using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp, pr, ar\n\n kainate (glutamate; [³H]kainate): fp, pr, ar\n\nNMDA (glutamate; [³H]MK-801): fp, pr, ar\n\nmGluR2/3 (glutamate; [³H] LY 341 495): fp, pr, ar\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp, pr, ar\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp, pr, ar\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp, pr, ar\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp, pr, ar\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp, pr, ar\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp, pr, ar\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp, pr, ar\n\nα₁ (noradrenalin; [³H]prazosin): fp, pr, ar\n\nα₂ (noradrenalin; [³H]UK-14,304): fp, pr, ar\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp, pr, ar\n\n5-HT₂ (serotonin; [³H]ketanserin): fp, pr, ar\n\nD₁ (dopamine; [³H]SCH23390): fp, pr, ar\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 7A"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area 7A",
+      "files": [
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+          "byteSize": 15996,
+          "name": "7A_fp_20180321.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_7A/7A_fp_20180321.xlsx",
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+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
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+          "contentType": "application/zip"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Grefkes, Christian",
+        "Scheperjans, Filip",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike"
+      ],
+      "kgReference": [
+        "10.25493/DQJ7-KC8"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        },
+        {
+          "name": "Transmitter receptors reveal segregation of cortical areas in the human superior parietal cortex: Relations to visual and somatosensory regions",
+          "cite": "Scheperjans, F., Palomero-Gallagher, N., Grefkes, C., Schleicher, A., & Zilles, K. (2005). Transmitter receptors reveal segregation of cortical areas in the human superior parietal cortex: Relations to visual and somatosensory regions. NeuroImage, 28(2), 362–379. ",
+          "doi": "10.1016/j.neuroimage.2005.06.028"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "png"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Evans, Alan C.",
+        "Amunts, Katrin"
+      ],
+      "description": "BigBrain is a ultrahigh-resolution three-dimensional (3D) model of a human brain at nearly cellular resolution of 20 micrometers, based on the reconstruction of 7404 histological sections. This dataset contains the reconstituted sections in the sagittal dimension. In addition, the final aligned sections in the coronal and axial dimension, and 3D histological volumes in histological space are also available.\n- Dataset \"[BigBrain High-resolution whole brain model: 2D Sections/Coronal](https://www.humanbrainproject.eu/en/explore-the-brain/search/#Dataset/1f50424206be7a0c1b8379bf8817be5e)\"\n- Dataset \"[BigBrain High-resolution whole brain model: 2D Sections/Axial](https://www.humanbrainproject.eu/en/explore-the-brain/search/#Dataset/c051f7cb18b7c998d815fcb71ed6b5d7)\"\n- Dataset \"[BigBrain High-resolution whole brain model: Downscaled volumes in minc and NIfTI format](https://www.humanbrainproject.eu/en/explore-the-brain/search/#Dataset/5cd7a689c75124a7455e1c31c9f478e0)\"",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "BigBrain High-resolution whole brain model: 2D Sections/Sagittal",
+      "files": [],
+      "contributors": [
+        "Amunts, Katrin",
+        "Evans, Alan C.",
+        "Zilles, Karl",
+        "Lippert, T.",
+        "Shah, Nadim J.",
+        "Oros-Peusquens, Ana-Maria",
+        "Lewis, Lindsay B.",
+        "Bazin, P.-L.",
+        "Bludau, Sebastian",
+        "Rousseau, M.-E.",
+        "Dickscheid, Timo",
+        "Mohlberg, Hartmut",
+        "Borgeat, L.",
+        "Lepage, Claude"
+      ],
+      "kgReference": [
+        "10.1126/science.1235381"
+      ],
+      "publications": [
+        {
+          "name": "BigBrain: An Ultrahigh-Resolution 3D Human Brain Model",
+          "cite": "Amunts, K., Lepage, C., Borgeat, L., Mohlberg, H., Dickscheid, T., Rousseau, M.-E., … Evans, A. C. (2013). BigBrain: An Ultrahigh-Resolution 3D Human Brain Model. Science, 340(6139), 1472–1475. ",
+          "doi": "10.1126/science.1235381"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Middle Temporal and Superior Temporal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_MT-ST_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_MT-ST_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
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+        {
+          "byteSize": 68240520,
+          "name": "lh_MT-ST_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_MT-ST_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Precentral and Superior Frontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_PrC-SF_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_PrC-SF_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
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+          "byteSize": 68240520,
+          "name": "lh_PrC-SF_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_PrC-SF_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "Nifti Files, gifti files, csv files, json files"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Thirion, Bertrand"
+      ],
+      "description": "This dataset contains functional magnetic resonance images (fMRIs) of 12 subjects that investigates cognitive-emotional processes on perception of faces and expressions. The paradigm was arranged in blocks that comprised sets of trials. Two categories of conditions can be highlighted from the paradigm: (1) the face-task category and (2) the eye-task category. Both categories involved self-reply according to the stimulus presented at every condition. The face-task category consisted in the presentation of human faces, whereas the eye-task category was dedicated to images representing human eyes. For the face-task category, two conditions corresponded to evaluation of gender and trustworthiness of the human faces. In the eye-task category, the two homologous conditions referred to gender and emotion-expression evaluation. The task concerning emotion expression in the latter category was in accordance with a cue given immediately before the image display. Besides, there was also a baseline condition, common to both categories, showing a grayscale grid image that may be tilted or not. To achieve the intended goal of this condition, a mental assessment about the orientation of the image had to be performed. The task consisted of twelve blocks per run, and every block comprised between two and four trials. The order of trials presentation was pseudorandomized for the session, but fixed for all participants. The trials lasted about 6.3 seconds. A fixation-cross period of approximately one second was presented between blocks.\n\n[https://openfmri.org/dataset/ds000244/](https://openfmri.org/dataset/ds000244/)\n\n[https://neurovault.org/collections/2138/](https://neurovault.org/collections/2138/)",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Individual Brain Charting: ARCHI emotional",
+      "files": [
+        {
+          "byteSize": 1298,
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+        "Thirion, Bertrand",
+        "Hertz-Pannier, Lucie",
+        "Dehaene, Stanislas",
+        "Pallier, Christophe",
+        "Varoquaux, Gaël",
+        "Eger, Evelyn",
+        "Pinel, Philippe",
+        "Martins, Bernadette",
+        "Doublé, Christine",
+        "Médiouni-Cloarec, Gaëlle",
+        "Joly-Testault, Véronique",
+        "Laurier, Laurence",
+        "Roger, Séverine",
+        "Becuwe-Desmidt, Séverine",
+        "Ginisty, Chantal",
+        "Denghien, Isabelle",
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+        "Ruest, Torsten",
+        "Amadon, Alexis"
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+        "Morosan, Patricia",
+        "Schleicher, Axel",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike",
+        "Zilles, Karl"
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+          "doi": "10.1016/j.cortex.2014.07.007"
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+        "Friederici, Angela D.",
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+        "Palomero-Gallagher, Nicola",
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+          "name": "MNI Colin 27"
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+        "Amunts, Katrin",
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+        "Mohlberg, Hartmut",
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+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Postcentral and Insula gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
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+        "Mangin, Jean-François",
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+        "Duclap, Delphine",
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+        "Román, Claudio"
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+      "licenseInfo": [
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+        "Guevara, Pamela",
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+        "Duclap, Delphine",
+        "Houenou, Josselin",
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+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
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+      "custodians": [
+        "Merchan-Perez, Angel"
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+      "description": "Data on synapses in the somatosensory cortex of the adult mouse, obtained with three-dimensional electron microscopy (FIB-SEM).\n**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
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+        "DeFelipe, Javier",
+        "Rodriguez, Rodrigo",
+        "Turegano, Marta"
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+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
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+        "Free"
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+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Schormann, Thorsten",
+        "Mohlberg, Hartmut",
+        "Malikovic, Aleksandar"
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+          "doi": "10.1006/nimg.1999.0516"
+        }
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+      "description": "Reconstruction of the hippocampus of a Thy1-GFP-M transgenic mouse, where a subset of pyramidal neurons and of interneurons are labeled. Data obtained with serial two-photon tomography.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
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+        "Free"
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+        "Silvestri, Ludovico"
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+        "10.25493/PMDH-FW1"
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+        "NIFTI"
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+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
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+      "description": "This dataset contains the distinct architectonic Fastigial Nucleus (Cerebellum) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Fastigial Nucleus (Cerebellum). The probability map of Fastigial Nucleus (Cerebellum) is given in file jubrain-pmap-v22c_space-mnicolin27_Cerebellum-Nfast.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Fastigial Nucleus (Cerebellum)"
+        }
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+      ],
+      "contributors": [
+        "Mohlberg, Hartmut",
+        "Amunts, Katrin",
+        "Minnerop, Martina",
+        "Eickhoff, Simon B.",
+        "Bludau, Sebastian",
+        "Tellmann, Stefanie"
+      ],
+      "kgReference": [
+        "10.25493/JNN1-V3Q"
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+      "publications": [
+        {
+          "name": "Cytoarchitectonic mapping of the human brain cerebellar nuclei in stereotaxic space and delineation of their co-activation patterns",
+          "cite": "Tellmann, S., Bludau, S., Eickhoff, S., Mohlberg, H., Minnerop, M., & Amunts, K. (2015). Cytoarchitectonic mapping of the human brain cerebellar nuclei in stereotaxic space and delineation of their co-activation patterns. Frontiers in Neuroanatomy, 09. ",
+          "doi": "10.3389/fnana.2015.00054"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
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+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area 5M (SPL) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area 5M (SPL). The probability map of Area 5M (SPL) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-5M.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 5M (SPL)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area 5M (SPL)",
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+          "contentType": "application/octet-stream"
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+      ],
+      "contributors": [
+        "Scheperjans, Filip",
+        "Schleicher, Axel",
+        "Amunts, Katrin",
+        "Hoemke, L.",
+        "Mohlberg, Hartmut",
+        "Zilles, Karl",
+        "Hermann, K.",
+        "Eickhoff, Simon B."
+      ],
+      "kgReference": [
+        "10.25493/CG41-Q6U"
+      ],
+      "publications": [
+        {
+          "name": "Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Eickhoff, S. B., Hoemke, L., Mohlberg, H., Hermann, K., Amunts, K., & Zilles, K. (2008). Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex. Cerebral Cortex, 18(9), 2141–2157. ",
+          "doi": "10.1093/cercor/bhm241"
+        },
+        {
+          "name": "Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Hermann, K., Eickhoff, S. B., Amunts, K., Schleicher, A., & Zilles, K. (2007). Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex. Cerebral Cortex, 18(4), 846–867. ",
+          "doi": "10.1093/cercor/bhm116"
+        }
+      ]
+    },
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+          "name": "Allen adult mouse brain reference atlas V2"
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+      "custodians": [
+        "Jankowsky, Joanna L."
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+      "description": "Bright-field microscopy images of serial horizontal brain sections showing neuropsin (Nop) promoter expression in a bigenic Nop-tetracycline-transactivator (tTA) mouse brain (case 2877, adult male), using a driver-reporter construct in which the Nop-tTA promoter regulates the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, which is visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Methodological details are provided in Yetman et al., Brain Struct Funct 221:2231-49, 2016. Our data show that the Nop-tTA promoter mainly is expressed in the entorhinal cortex, but also in several other cortical regions.",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
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+      "name": "Neuropsin tetracycline-transactivator expression: horizontal sections (case 2877)",
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+      "contributors": [
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+        "Leergaard, Trygve B.",
+        "Lillehaug, Sveinung",
+        "Jankowsky, Joanna L.",
+        "Bjaalie, Jan G."
+      ],
+      "kgReference": [
+        "10.25493/AYBB-BXV"
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+      "publications": [
+        {
+          "name": "Transgene expression in the Nop-tTA driver line is not inherently restricted to the entorhinal cortex",
+          "cite": "Yetman, M. J., Lillehaug, S., Bjaalie, J. G., Leergaard, T. B., & Jankowsky, J. L. (2015). Transgene expression in the Nop-tTA driver line is not inherently restricted to the entorhinal cortex. Brain Structure and Function, 221(4), 2231–2249. ",
+          "doi": "10.1007/s00429-015-1040-9"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [
+        {
+          "name": "Waxholm Space rat brain atlas v.2.0"
+        }
+      ],
+      "custodians": [
+        "Leergaard, Trygve B."
+      ],
+      "description": "Brain-wide serial microscopic images of coronal and sagittal rat brain sections stained with thionine to visualize cytoarchitecture, or with Woelche's myelin staining method to visualize myeloarchitecture.",
+      "licenseInfo": [
+        "Creative Commons Attribution-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Atlas of normal rat brain cyto- and myeloarchitecture",
+      "files": [],
+      "contributors": [
+        "Lillehaug, Sveinung",
+        "Leergaard, Trygve B.",
+        "Bjaalie, Jan G.",
+        "Dale, Anders M."
+      ],
+      "kgReference": [
+        "10.25493/C63A-FEY"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Pars Orbitalis and Insula gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_Or-Ins_0"
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
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+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
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+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Middle Temporal and Supramarginal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_MT-SM_0"
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+      "name": "Probabilistic maps of rh_MT-SM_0",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
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+          "byteSize": 68240520,
+          "name": "rh_MT-SM_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_MT-SM_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "DeFelipe, Javier"
+      ],
+      "description": "Density and distribution of different types of cells in the somatosensory cortex in fixed brains.   \n \n**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Embargoed"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Cell density and distribution in the somatosensory cortex of the mouse brain",
+      "files": [],
+      "contributors": [
+        "Alonso-Nanclares, Lidia",
+        "Tapia,Silvia",
+        "Garcia,Ana",
+        "Fernaud,Isabel",
+        "Muñoz,Alberto",
+        "Anton, Alejandro",
+        "Cano, Deborah",
+        "Alvarez, Carmen"
+      ],
+      "kgReference": [
+        "10.25493/4HFC-6ZX"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area 7PC (SPL) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area 7PC (SPL). The probability map of Area 7PC (SPL) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-7PC.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 7PC (SPL)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area 7PC (SPL)",
+      "files": [
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
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+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-7PC.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-7PC.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Scheperjans, Filip",
+        "Eickhoff, Simon B.",
+        "Hoemke, L.",
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Hermann, K."
+      ],
+      "kgReference": [
+        "10.25493/27J7-2YX"
+      ],
+      "publications": [
+        {
+          "name": "Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Hermann, K., Eickhoff, S. B., Amunts, K., Schleicher, A., & Zilles, K. (2007). Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex. Cerebral Cortex, 18(4), 846–867. ",
+          "doi": "10.1093/cercor/bhm116"
+        },
+        {
+          "name": "Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Eickhoff, S. B., Hoemke, L., Mohlberg, H., Hermann, K., Amunts, K., & Zilles, K. (2008). Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex. Cerebral Cortex, 18(9), 2141–2157. ",
+          "doi": "10.1093/cercor/bhm241"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Lateral Orbitofrontal and Rostral Middle Frontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_LOF-RMF_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_LOF-RMF_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "lh_LOF-RMF_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_LOF-RMF_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area ifs4 (IFS) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area ifs4 (IFS). The probability map of  Area ifs4 (IFS) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-ifs4.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area ifs4 (IFS)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area ifs4 (IFS)",
+      "files": [],
+      "contributors": [
+        "Bradler, Sabine",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area PFop using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp\n\nkainate (glutamate; [³H]kainate): fp\n\nNMDA (glutamate; [³H]MK-801): fp\n\nmGluR2/3 (glutamate; [³H] LY 341 495): fp\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp\n\nα₁ (noradrenalin; [³H]prazosin): fp\n\nα₂ (noradrenalin; [³H]UK-14,304): fp\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp\n\n5-HT₂ (serotonin; [³H]ketanserin): fp\n\nD₁ (dopamine; [³H]SCH23390): fp\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area PFop"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area PFop",
+      "files": [
+        {
+          "byteSize": 16283,
+          "name": "PFop_fp_20180405.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_PFop/PFop_fp_20180405.xlsx",
+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        },
+        {
+          "byteSize": 44096,
+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Caspers, S.",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike"
+      ],
+      "kgReference": [
+        "10.25493/9G1P-02S"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        },
+        {
+          "name": "Organization of the Human Inferior Parietal Lobule Based on Receptor Architectonics",
+          "cite": "Caspers, S., Schleicher, A., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Zilles, K. (2012). Organization of the Human Inferior Parietal Lobule Based on Receptor Architectonics. Cerebral Cortex, 23(3), 615–628. ",
+          "doi": "10.1093/cercor/bhs048"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "Nifti Files, gifti files, csv files, json files"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Thirion, Bertrand"
+      ],
+      "description": "This dataset contains functional magnetic resonance images (fMRIs) of 12 subjects performing HCP Relational task that employed a relational match-to-sample paradigm, featuring a second-order comparison of relations between two pairs of objects. It served primarily as a localizer of the rostrolateral prefrontal cortex, since relational matching mechanisms have been shown to yield activity in this region. Similar to some previous tasks, the paradigm included two categories of blocks, namely relational-processing and control-matching blocks. All blocks were constituted by a set of events. In the relational-processing block, visual stimuli consisted of images representing two pairs of objects, in which one pair was placed at the top and the other one at the bottom of the image, respectively. Objects within a pair may differ in two features: shape and texture. The participants had to identify whether the pair of objects from the top differed in a specific feature and, subsequently, they were asked to determine whether the pair from the bottom changed along the same feature. For the control block, one pair of objects was displayed at the top of the image and a single object at the bottom of the same image. In addition, a cue was shown in the middle of that image, indicating which feature is relevant. The participants had thus to indicate whether the object from the bottom was matching either of the two objects from the top, according to the feature specified as a cue. This task included twelve blocks per run, with six blocks per category. Block categories were, in turn, interleaved for display within a run. A fixation-cross period of sixteen seconds was inserted between some blocks. All blocks contained six trials and they were always initiated by a cue of two seconds. The trials were described by a visual-stimulus plus response period followed by a fixation-cross period, lasting up to ten seconds. The duration of the former was nine seconds and 7.6 seconds during the relational-processing block and controlmatching block, respectively.\n\n[https://openfmri.org/dataset/ds000244/](https://openfmri.org/dataset/ds000244/)\n\n[https://neurovault.org/collections/2138/](https://neurovault.org/collections/2138/)",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Individual Brain Charting: HCP Relational task",
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+          "contentType": "application/octet-stream"
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+      ],
+      "contributors": [
+        "Pinho, Ana Luísa",
+        "Thirion, Bertrand",
+        "Hertz-Pannier, Lucie",
+        "Dehaene, Stanislas",
+        "Pallier, Christophe",
+        "Varoquaux, Gaël",
+        "Eger, Evelyn",
+        "Pinel, Philippe",
+        "Martins, Bernadette",
+        "Doublé, Christine",
+        "Médiouni-Cloarec, Gaëlle",
+        "Joly-Testault, Véronique",
+        "Laurier, Laurence",
+        "Roger, Séverine",
+        "Becuwe-Desmidt, Séverine",
+        "Ginisty, Chantal",
+        "Denghien, Isabelle",
+        "Dohmatob, Elvis",
+        "Fabre, Murielle",
+        "Ruest, Torsten",
+        "Amadon, Alexis"
+      ],
+      "kgReference": [
+        "10.25493/WQAG-ZDZ"
+      ],
+      "publications": [
+        {
+          "name": "Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping",
+          "cite": "Pinho, A. L., Amadon, A., Ruest, T., Fabre, M., Dohmatob, E., Denghien, I., … Thirion, B. (2018). Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping. Scientific Data, 5, 180105. ",
+          "doi": "10.1038/sdata.2018.105"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Lateral Orbitofrontal and Pars Orbitalis gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_LOF-Or_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_LOF-Or_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
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+          "name": "lh_LOF-Or_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_LOF-Or_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
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+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area PF using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp\n\nkainate (glutamate; [³H]kainate): fp\n\nNMDA (glutamate; [³H]MK-801): fp\n\nmGluR2/3 (glutamate; [³H] LY 341 495): fp\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp\n\nα₁ (noradrenalin; [³H]prazosin): fp\n\nα₂ (noradrenalin; [³H]UK-14,304): fp\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp\n\n5-HT₂ (serotonin; [³H]ketanserin): fp\n\nD₁ (dopamine; [³H]SCH23390): fp\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area PF"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area PF",
+      "files": [
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+          "name": "PF_fp_20180405.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_PF/PF_fp_20180405.xlsx",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Caspers, S.",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike"
+      ],
+      "kgReference": [
+        "10.25493/VSFY-EYF"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        },
+        {
+          "name": "Organization of the Human Inferior Parietal Lobule Based on Receptor Architectonics",
+          "cite": "Caspers, S., Schleicher, A., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Zilles, K. (2012). Organization of the Human Inferior Parietal Lobule Based on Receptor Architectonics. Cerebral Cortex, 23(3), 615–628. ",
+          "doi": "10.1093/cercor/bhs048"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Posterior Cingulate and Rostral Anterior Cingulate gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_PoCi-RAC_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_PoCi-RAC_0",
+      "files": [
+        {
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+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
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+          "name": "lh_PoCi-RAC_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_PoCi-RAC_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Activity-dependent changes of spine proteomes",
+      "files": [],
+      "contributors": [
+        "Marinelli, Silvia",
+        "Pizzarelli, Rocco"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Pars Opercularis and Superior Frontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_Op-SF_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_Op-SF_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
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+          "name": "rh_Op-SF_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_Op-SF_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area ifj1 (IFS/PreS) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area ifj1 (IFS/PreS). The probability map of  Area ifj1 (IFS/PreS) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-ifj1.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area ifj1 (IFS/PreS)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area ifj1 (IFS/PreS)",
+      "files": [],
+      "contributors": [
+        "Bradler, Sabine",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Lateral Orbitofrontal and Superior Temporal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_LOF-ST_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_LOF-ST_0",
+      "files": [
+        {
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+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "rh_LOF-ST_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_LOF-ST_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Pars Opercularis and Superior Frontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_Op-SF_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_Op-SF_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
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+          "name": "lh_Op-SF_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_Op-SF_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "png"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Evans, Alan C.",
+        "Amunts, Katrin"
+      ],
+      "description": "BigBrain is a ultrahigh-resolution three-dimensional (3D) model of a human brain at nearly cellular resolution of 20 micrometers, based on the reconstruction of 7404 histological sections. This dataset contains the reconstituted sections in the coronal dimension. In addition, the final aligned sections in the axial and sagittal dimension, and 3D histological volumes in histological space are also available.\n- Dataset \"[BigBrain High-resolution whole brain model: 2D Sections/Axial](https://www.humanbrainproject.eu/en/explore-the-brain/search/#Dataset/c051f7cb18b7c998d815fcb71ed6b5d7)\"\n- Dataset \"[BigBrain High-resolution whole brain model: 2D Sections/Sagittal](https://www.humanbrainproject.eu/en/explore-the-brain/search/#Dataset/9e36fc587ce8193795137371a85a351e)\"\n- Dataset \"[BigBrain High-resolution whole brain model: Downscaled volumes in minc and NIfTI format](https://www.humanbrainproject.eu/en/explore-the-brain/search/#Dataset/5cd7a689c75124a7455e1c31c9f478e0)\"",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "BigBrain High-resolution whole brain model: 2D Sections/Coronal",
+      "files": [],
+      "contributors": [
+        "Amunts, Katrin",
+        "Evans, Alan C.",
+        "Zilles, Karl",
+        "Lippert, T.",
+        "Shah, Nadim J.",
+        "Oros-Peusquens, Ana-Maria",
+        "Lewis, Lindsay B.",
+        "Bazin, P.-L.",
+        "Bludau, Sebastian",
+        "Rousseau, M.-E.",
+        "Dickscheid, Timo",
+        "Mohlberg, Hartmut",
+        "Borgeat, L.",
+        "Lepage, Claude"
+      ],
+      "kgReference": [
+        "10.1126/science.1235381"
+      ],
+      "publications": [
+        {
+          "name": "BigBrain: An Ultrahigh-Resolution 3D Human Brain Model",
+          "cite": "Amunts, K., Lepage, C., Borgeat, L., Mohlberg, H., Dickscheid, T., Rousseau, M.-E., … Evans, A. C. (2013). BigBrain: An Ultrahigh-Resolution 3D Human Brain Model. Science, 340(6139), 1472–1475. ",
+          "doi": "10.1126/science.1235381"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "electrophysiological data",
+        "xml"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "<Unknown>"
+        }
+      ],
+      "custodians": [
+        "Brochier, Thomas",
+        "Denker, Michael",
+        "Zehl, Lyuba",
+        "Riehle, Alexa"
+      ],
+      "description": "We provide two electrophysiological datasets recorded via a 10-by-10 multi-electrode array chronically implanted in the motor cortex of two macaque monkeys during an instructed delayed reach-to-grasp task. The datasets contain the continuous measure of extracellular potentials at each electrode sampled at 30 kHz, the local field potentials sampled at 1 kHz and the timing of the online and offline extracted spike times. It also includes the timing of several task-related and behavioral events recorded along with the electrophysiological data. Finally, the datasets provide a complete set of metadata structured in a standardized format. These metadata allow easy access to detailed information about the datasets such as the settings of the recording hardware, the array specifications, the location of the implant in the motor cortex, information about the monkeys, or the offline spike sorting. The two datasets can be exploited to address crucial issues in neurophysiology such as: What are the principles of neural interactions in a local cortical network and how are these interactions modulated during a well-described behavioral task? How different neuronal signals such as single-unit activity, multi-unit activity or LFPs relate to each other? Which spike sorting methods provide the best estimate of single unit activity? The dataset is explain in detail in: Brochier, T., Zehl, L., Hao, Y., Duret, M., Sprenger, J., Denker, M., Grün, S., and Riehle, A. (2018). Massively parallel recordings in macaque motor cortex during an instructed delayed reach-to-grasp task. Scientific Data 5, 180055.",
+      "licenseInfo": [],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [
+        {
+          "name": "Dorsolateral Motor Cortex"
+        },
+        {
+          "name": "Dorsolateral Premotor Cortex"
+        }
+      ],
+      "name": "Massively parallel multi-electrode recordings of macaque motor cortex during an instructed delayed reach-to-grasp task",
+      "files": [],
+      "contributors": [
+        "Brochier, Thomas",
+        "Riehle, Alexa",
+        "Grün, Sonja",
+        "Denker, Michael",
+        "Sprenger, Julia",
+        "Duret, Margaux",
+        "Hao, Yaoyao",
+        "Zehl, Lyuba"
+      ],
+      "kgReference": [
+        "10.12751/g-node.f83565"
+      ],
+      "publications": [
+        {
+          "name": "Massively parallel recordings in macaque motor cortex during an instructed delayed reach-to-grasp task",
+          "cite": "Brochier, T., Zehl, L., Hao, Y., Duret, M., Sprenger, J., Denker, M., … Riehle, A. (2018). Massively parallel recordings in macaque motor cortex during an instructed delayed reach-to-grasp task. Scientific Data, 5, 180055. ",
+          "doi": "10.1038/sdata.2018.55"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Caudal Middle Frontal and Superior Frontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_CMF-SF_1"
+        }
+      ],
+      "name": "Probabilistic maps of rh_CMF-SF_1",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "rh_CMF-SF_1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_CMF-SF_1.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
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+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area s24 (sACC) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Area s24 (sACC). The probability map of Area s24 (sACC) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-s24.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area s24 (sACC)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area s24 (sACC)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-s24.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-s24.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Mohlberg, Hartmut",
+        "Zilles, Karl",
+        "Amunts, Katrin",
+        "Vogt, Brent A.",
+        "Schleicher, Axel",
+        "Hoffstaedter, Felix",
+        "Eickhoff, Simon B.",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "kgReference": [
+        "10.25493/FQ3R-3JX"
+      ],
+      "publications": [
+        {
+          "name": "Functional organization of human subgenual cortical areas: Relationship between architectonical segregation and connectional heterogeneity",
+          "cite": "Palomero-Gallagher, N., Eickhoff, S. B., Hoffstaedter, F., Schleicher, A., Mohlberg, H., Vogt, B. A., … Zilles, K. (2015). Functional organization of human subgenual cortical areas: Relationship between architectonical segregation and connectional heterogeneity. NeuroImage, 115, 177–190. ",
+          "doi": "10.1016/j.neuroimage.2015.04.053"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Inferior Parietal and Supramarginal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_IP-SM_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_IP-SM_0",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "lh_IP-SM_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_IP-SM_0.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Storm, Johan"
+      ],
+      "description": "The aim of this task is to develop a protocol and a set-up for recording EEG signal from a large number of cortical areas in head-restrained rats exposed to anesthesia and during wakefulness. In order to quantify cortical complexity and its relation to (un)consciousness, a large scale EEG that samples activity from most of cortical areas is needed (Massimini et al. Science, 2005; Casali et al. Sci Transl Med, 2013). Unfortunately, only few existing probes allow this large scale recording in rodents (Megévand et al. Neuroimage, 2008; Choi et al. J Neurophysiol, 2010). Besides, since those probes are designed to be laid down on the skull surface, the obtained scalp EEG is subjected to the filtering action of the skull tissue, which separates the brain surface from the electrode. This would reduce the amplitude and the high frequency resolution of the cortical signal (Buzsàki et al. Nat Rev Neuroscience, 2012). Alternatively, epidural screw electrodes, by directly contacting the outer surface of the dura mater, showed a high signal amplitude and resolution, even for high frequencies (Arena et al. J Physiol, 2016). Therefore, we expanded the spatial density of epidural electrodes and optimized a protocol for the surgical implantation of a chronic array of 17 stainless steel electrodes by covering most of the cortical areas of a rat brain. Then, in combination with protocol for head restraining (Moore et al. Nat Protocols, 2014), we obtained multi-channel spontaneous EEG recordings from rats during wakefulness and during the exposure to low and high doses of 3 different anesthetics (propofol, sevoflurane and ketamine).   \n\n**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial 4.0 International"
+      ],
+      "embargoStatus": [
+        "Embargoed"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Large scale multi-channel EEG in rats",
+      "files": [],
+      "contributors": [
+        "Alessandro, Arena",
+        "Storm, Johan"
+      ],
+      "kgReference": [
+        "10.25493/4SPM-V00"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Inferior Parietal and Superior Parietal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_IP-SP_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_IP-SP_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "rh_IP-SP_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_IP-SP_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "A general procedure to fit individual synaptic events recorded from voltage clamp experiments was tested with various sets of experimental data on GABAergic synapses; gephyrin and gephyrin-dependent pathways were chosen as a suitable example of a kinetic model of synaptic transmission.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Action potential dependent sIPSCs - from juvenile (P21-30) C57Bl6/J male mice",
+      "files": [],
+      "contributors": [
+        "Marchetti, Cristina",
+        "Marinelli, Silvia",
+        "Cherubini, Enrico"
+      ],
+      "kgReference": [
+        "10.25493/H57G-ZK5"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area 1 (PostCG) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area 1 (PostCG). The probability map of Area 1 (PostCG) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-1.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 1 (PostCG)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area 1 (PostCG)",
+      "files": [
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-1.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Geyer, Stefan",
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Schormann, Thorsten",
+        "Mohlberg, Hartmut"
+      ],
+      "kgReference": [
+        "10.25493/3D29-NJ7"
+      ],
+      "publications": [
+        {
+          "name": "Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex",
+          "cite": "Geyer, S., Schormann, T., Mohlberg, H., & Zilles, K. (2000). Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex. NeuroImage, 11(6), 684–696. ",
+          "doi": "10.1006/nimg.2000.0548"
+        },
+        {
+          "name": "Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex",
+          "cite": "Geyer, S., Schleicher, A., & Zilles, K. (1999). Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex. NeuroImage, 10(1), 63–83. ",
+          "doi": "10.1006/nimg.1999.0440"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "DeFelipe, Javier"
+      ],
+      "description": "**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Synapse maps - FIBSEM",
+      "files": [],
+      "contributors": [
+        "Benevides, Ruth",
+        "Gonzalez, Santiago",
+        "Valdes, Lorena",
+        "Tapia, Silvia",
+        "Rodriguez, Rodrigo",
+        "DeFelipe, Javier",
+        "Merchan-Perez, Angel",
+        "Alvarez, Carmen",
+        "Santuy, Andrea",
+        "Kastanauskaite, Asta",
+        "Muñoz, A"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area Fp1 (Fpole) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Area Fp1 (Fpole). The probability map of Area Fp1 (Fpole) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-Fp1.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area Fp1 (Fpole)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area Fp1 (Fpole)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-Fp1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-Fp1.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Bludau, Sebastian",
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Fox, P.T.",
+        "Laird, A.R.",
+        "Caspers, S.",
+        "Mohlberg, Hartmut",
+        "Eickhoff, Simon B."
+      ],
+      "kgReference": [
+        "10.25493/RPDP-VMG"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitecture, probability maps and functions of the human frontal pole",
+          "cite": "Bludau, S., Eickhoff, S. B., Mohlberg, H., Caspers, S., Laird, A. R., Fox, P. T., … Amunts, K. (2014). Cytoarchitecture, probability maps and functions of the human frontal pole. NeuroImage, 93, 260–275. ",
+          "doi": "10.1016/j.neuroimage.2013.05.052"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
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+      "custodians": [
+        "Poupon, Cyril"
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+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Inferior Parietal and Lateral Occipital gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
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+      "license": [],
+      "parcellationRegion": [
+        {
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+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
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+          "name": "MNI Colin 27"
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+      "custodians": [
+        "Amunts, Katrin"
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+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area Fo3 (OFC)"
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+      "name": "Probabilistic cytoarchitectonic map of Area Fo3 (OFC)",
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Mohlberg, Hartmut",
+        "Amunts, Katrin",
+        "Bludau, Sebastian",
+        "Eickhoff, Simon B.",
+        "Gerboga, Fatma",
+        "Schleicher, Axel",
+        "Palomero-Gallagher, Nicola",
+        "Zilles, Karl",
+        "Henssen, Anton"
+      ],
+      "kgReference": [
+        "10.25493/9ZWB-EEZ"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitecture and probability maps of the human medial orbitofrontal cortex",
+          "cite": "Henssen, A., Zilles, K., Palomero-Gallagher, N., Schleicher, A., Mohlberg, H., Gerboga, F., … Amunts, K. (2016). Cytoarchitecture and probability maps of the human medial orbitofrontal cortex. Cortex, 75, 87–112. ",
+          "doi": "10.1016/j.cortex.2015.11.006"
+        }
+      ]
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+      "formats": [
+        "Nifti Files, gifti files, csv files, json files"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Thirion, Bertrand"
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+      "description": "This dataset contains functional magnetic resonance images (fMRIs) of 12 subjects performing HCP Gambling task. Its aim was to localize brain structures of the reward system, namely the basal ganglia complex. The paradigm included eight blocks and each block was composed of eight events. For every event, the participants were asked to play a game. The goal was to guess whether the next number to be displayed, which ranged from one to nine, would be smaller or larger than five while a question mark was shown on the screen. The answer was given by pressing the respective button of the response box. Feedback on the correct number was provided afterwards. There was an equal amount of blocks; the participants experienced a majority of either reward or loss events in each of them. The task was constituted by eight blocks per run, in which each half related to reward and loss experience, respectively. The order of the two block cate gories was pseudo-randomized during a single run, but fixed for all participants. A fixation-cross period of fifteen seconds was displayed between blocks. All blocks contained eight trials. The trials included a question-mark visual stimulus lasting up to 1.5 seconds, a feedback period of one second and a fixation-cross period of one second, as well; the total duration of the trial was then 3.5 seconds approximately.\n\n[https://openfmri.org/dataset/ds000244/](https://openfmri.org/dataset/ds000244/)\n\n[https://neurovault.org/collections/2138/](https://neurovault.org/collections/2138/)",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Individual Brain Charting: HCP Gambling task",
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+        "Varoquaux, Gaël",
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+        "Pinel, Philippe",
+        "Martins, Bernadette",
+        "Doublé, Christine",
+        "Médiouni-Cloarec, Gaëlle",
+        "Joly-Testault, Véronique",
+        "Laurier, Laurence",
+        "Roger, Séverine",
+        "Becuwe-Desmidt, Séverine",
+        "Ginisty, Chantal",
+        "Denghien, Isabelle",
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+          "cite": "Pinho, A. L., Amadon, A., Ruest, T., Fabre, M., Dohmatob, E., Denghien, I., … Thirion, B. (2018). Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping. Scientific Data, 5, 180105. ",
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+        "Zilles, Karl",
+        "Schneider, F.",
+        "Habel, U.",
+        "Mohlberg, Hartmut",
+        "Pieperhoff, P.",
+        "Kindler, M.",
+        "Kedo, O.",
+        "Amunts, Katrin"
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+          "cite": "Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N. J., … Zilles, K. (2005). Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and Embryology, 210(5-6), 343–352. ",
+          "doi": "10.1007/s00429-005-0025-5"
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+      "parcellationRegion": [
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000043/EPhys_Morpho_Human_PYR.zip",
+          "contentType": "application/zip"
+        }
+      ],
+      "contributors": [
+        "de Kock, Christiaan P.J.",
+        "Mansvelder, Huibert D.",
+        "Segev, Idan",
+        "Baayen, Johannes C.",
+        "Narayanan, Rajeevan T.",
+        "Boudewijns, Zimbo S.R.M.",
+        "Obermayer, Joshua",
+        "Testa-Silva, Guilherme",
+        "van der Sluis, Sophie",
+        "Groot, Colin",
+        "Asamoah, Boateng",
+        "Goriounova, Natalia A.",
+        "Lodder, Brendan N.",
+        "Aardse, Romy",
+        "Eyal, Guy",
+        "Doreswamy, Keerthi K.",
+        "Verhoog, Matthijs B.",
+        "Mohan, Hemanth"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Dendritic and Axonal Architecture of Individual Pyramidal Neurons across Layers of Adult Human Neocortex",
+          "cite": "Mohan, H., Verhoog, M. B., Doreswamy, K. K., Eyal, G., Aardse, R., Lodder, B. N., … de Kock, C. P. J. (2015). Dendritic and Axonal Architecture of Individual Pyramidal Neurons across Layers of Adult Human Neocortex. Cerebral Cortex, 25(12), 4839–4853. ",
+          "doi": "10.1093/cercor/bhv188"
+        },
+        {
+          "name": "Comprehensive Morpho-Electrotonic Analysis Shows 2 Distinct Classes of L2 and L3 Pyramidal Neurons in Human Temporal Cortex",
+          "cite": "Deitcher, Y., Eyal, G., Kanari, L., Verhoog, M. B., Atenekeng Kahou, G. A., Mansvelder, H. D., … Segev, I. (2017). Comprehensive Morpho-Electrotonic Analysis Shows 2 Distinct Classes of L2 and L3 Pyramidal Neurons in Human Temporal Cortex. Cerebral Cortex, 27(11), 5398–5414. ",
+          "doi": "10.1093/cercor/bhx226"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "A general procedure to fit individual synaptic events recorded from voltage clamp experiments was tested with various sets of experimental data on GABAergic synapses; gephyrin and gephyrin-dependent pathways were chosen as a suitable example of a kinetic model of synaptic transmission. The data used here are obtained from coronal hippocampal slices (300 μm thick) from 3-4 months old wt (B6/SJL) female mice. The dataset contains 701 individual events recorded from 7 different neurons (expB1-B7).\nThe first column of each txt file contains the time in ms and the other columns contain spontaneous inhibitory synaptic currents (sIPSCs) in pA.\nComputational modeling of brain circuits requires the definition of many parameters that are difficult to determine from experimental findings. One way to help interpret these data is to fit them using a particular kinetic model. In [1] we proposed a general procedure to fit individual synaptic events recorded from voltage clamp experiments. Starting from any given model description (mod file) in the NEURON simulation environment, the procedure exploits user-defined constraints, dependencies, and rules for the parameters of the model to fit the time course of individual spontaneous synaptic events that are recorded experimentally. A Python version is available for public use, as a Jupyter Notebook in the Collaboratory Portal of the Human Brain Project. To illustrate the potential application of the procedure, we tested its use with various sets of experimental data on GABAergic synapses; gephyrin and gephyrin-dependent pathways were chosen as a suitable example of a kinetic model of synaptic transmission. For individual spontaneous inhibitory events in hippocampal pyramidal CA1 neurons, we found that gephyrin-dependent subcellular pathways may shape synaptic events at different levels, and can be correlated with cell- or event-specific activity history and/or pathological conditions.\nFitting experimental data against a number of different models is a common way to do this (reviewed in [2]), and can help in the subsequent interpretation of the data. In general, experimental traces are fitted using specific approaches for specific purposes (e.g., [3], [4]). However, to the best of our knowledge, there is no easy, user-friendly, general procedure available for this purpose, especially in computational neuroscience. Our aim was thus to identify the appropriate conceptual structure of a procedure to obtain good, reliable fits of raw experimental traces of spontaneous synaptic events. This is an important step because spontaneous synaptic events have been so far exclusively analyzed using traces obtained by averaging many events. However, as can be easily imagined, each synapse in any given neuron has its own, independent, history of activation. The most likely physiological consequence is that the variables relative to the subcellular processes underlying synaptic transmission are different for each synapse. If a researcher is interested in testing a specific kinetic scheme implemented for specific biochemical pathways, the use of individual events is the most appropriate choice, since this approach would give information on the different combinations of model parameters that are consistent with the observed events. Averaging traces will lose a lot of relevant information.\nWe therefore present here the implementation of a procedure leading to the development of a unifying optimization method for individual synaptic events. Experimental data, kinetic models of synaptic transmission, and fitting parameters and their dependencies can be user defined/provided or gathered from databases. They can be used to generate optimized groups of parameters able to represent a population of synapses, either for simulation purposes or to study the functional consequences of a particular protein or subcellular synaptic transmission pathway.\n[1] Lupascu CA, Morabito A, Merenda E, et al. A General Procedure to Study Subcellular Models of Transsynaptic Signaling at Inhibitory Synapses. Frontiers in Neuroinformatics. 2016;10:23. doi:10.3389/fninf.2016.00023  \n[2] Van Geit W., De Schutter E., Achard P. (2008). Automated neuron model optimization techniques: a review. Biol. Cybern. 99, 241–251. 10.1007/s00422-008-0257-6  \n[3] Bekkers J. M. (2003). Convolution of mini distributions for fitting evoked synaptic amplitude histograms. J. Neurosci. Methods. 130, 105–114. 10.1016/j.jneumeth.2003.09.018  \n[4] Meisl G., Kirkegaard J. B., Arosio P., Michaels T. C., Vendruscolo M., Dobson C. M., et al. . (2016). Molecular mechanisms of protein aggregation from global fitting of kinetic models. Nat. Protoc. 11, 252–272. 10.1038/nprot.2016.010",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Spontaneous inhibitory post-synaptic currents recorded from CA1 pyramidal neurons of adult wild type \nB6/SJL  mice",
+      "files": [],
+      "contributors": [
+        "Marinelli, Silvia",
+        "Cherubini, Enrico",
+        "Marchetti, Cristina"
+      ],
+      "kgReference": [
+        "10.25493/85F8-M92"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Precentral and Insula gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_PrC-Ins_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_PrC-Ins_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "lh_PrC-Ins_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_PrC-Ins_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [
+        {
+          "name": "Waxholm Space rat brain atlas v.2.0"
+        }
+      ],
+      "custodians": [
+        "D'Angelo, Egidio"
+      ],
+      "description": "Study of the synaptic responses of granule cells.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Loose-cell attached patch-clamp recordings from cerebellar granule cells",
+      "files": [],
+      "contributors": [
+        "D'Angelo, Egidio",
+        "Tognolina, Marialuisa"
+      ],
+      "kgReference": [
+        "10.25493/6R48-E3V"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Modulation of GABAergic currents by anti-neuroligin 2 and anti-gephyrin intrabodies (scFvGephcyto)",
+      "files": [],
+      "contributors": [
+        "Morabito, Annunziato",
+        "Giustizieri, Michela",
+        "Meli, Giovanni",
+        "Cherubini, Enrico",
+        "Cattaneo, Antonino",
+        "Marinelli, Silvia"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "nifti, Brainvisa Mesh, gifti, csv"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Dehaene-Lambertz, Ghislaine"
+      ],
+      "description": "The Infant brain template is a corrected three-dimensional reconstruction of a single MRI brain scan of a single human infant (female, age: 7.1 weeks) with a high resolution (1.1 mm isotropic). The inner cortical surface was segmented using a semi-automatic segmentation pipeline dedicated to T2-weighted MRI images of the infant brain, followed by manual correction, when local inaccuracies were detected. On the basis of the segmented sulci, 47 anatomical regions were delineated in each hemisphere, using the same principles as the AAL atlas (Automated Anatomical Labelling).",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Lateral ventricule and remaining tissues"
+        },
+        {
+          "name": "Thalamus"
+        },
+        {
+          "name": "Caudate"
+        },
+        {
+          "name": "Nuclei Putamen"
+        },
+        {
+          "name": "Anterior cingulate gyrus"
+        },
+        {
+          "name": "Middle cingulate gyrus"
+        },
+        {
+          "name": "Posterior cingulate gyrus"
+        },
+        {
+          "name": "Amygdala"
+        },
+        {
+          "name": "Limbic Parahippocampal gyrus"
+        },
+        {
+          "name": "Cuneus"
+        },
+        {
+          "name": "Calcarine sulcus"
+        },
+        {
+          "name": "Lingual gyrus"
+        },
+        {
+          "name": "Fusiform gyrus"
+        },
+        {
+          "name": "Superior occipital gyrus"
+        },
+        {
+          "name": "Middle occipital gyrus"
+        },
+        {
+          "name": "Inferior occipital gyrus"
+        },
+        {
+          "name": "Planum polare"
+        },
+        {
+          "name": "Planum temporale"
+        },
+        {
+          "name": "Planum parietale"
+        },
+        {
+          "name": "Heschl gyrus"
+        },
+        {
+          "name": "Superior temporal gyrus"
+        },
+        {
+          "name": "Middle temporal gyrus"
+        },
+        {
+          "name": "Inferior temporal gyrus"
+        },
+        {
+          "name": "Superior temporal pole"
+        },
+        {
+          "name": "Temporal Middle temporal pole"
+        },
+        {
+          "name": "Precuneus"
+        },
+        {
+          "name": "Superior parietal gyrus"
+        },
+        {
+          "name": "Inferior parietal gyrus"
+        },
+        {
+          "name": "Supramarginal gyrus"
+        },
+        {
+          "name": "Angular gyrus"
+        },
+        {
+          "name": "Paracentral lobule"
+        },
+        {
+          "name": "Postcentral gyrus"
+        },
+        {
+          "name": "Precentral gyrus"
+        },
+        {
+          "name": "Rolandic operculum"
+        },
+        {
+          "name": "Orbitary superior frontal gyrus"
+        },
+        {
+          "name": "Orbitary middle frontal gyrus"
+        },
+        {
+          "name": "Orbitary inferior frontal gyrus"
+        },
+        {
+          "name": "Orbitary frontal medial"
+        },
+        {
+          "name": "Gyrus rectus"
+        },
+        {
+          "name": "Olfactory bulb"
+        },
+        {
+          "name": "Supplementary motor area"
+        },
+        {
+          "name": "Medial superior frontal gyrus"
+        },
+        {
+          "name": "Superior frontal gyrus"
+        },
+        {
+          "name": "Middle frontal gyrus"
+        },
+        {
+          "name": "Inferior frontal gyrus, triangular part"
+        },
+        {
+          "name": "Inferior frontal gyrus, opercular part"
+        },
+        {
+          "name": "Insula"
+        }
+      ],
+      "name": "Corrected 3-D reconstruction and surface parcellation of an infant brain",
+      "files": [
+        {
+          "byteSize": 806639,
+          "name": "template_L.gii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Infant/infant-template/template_L.gii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 2281,
+          "name": "labeltable.csv",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Infant/infant-template/labeltable.csv",
+          "contentType": "text/csv"
+        },
+        {
+          "byteSize": 548781,
+          "name": "template_head.mesh",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Infant/infant-template/template_head.mesh",
+          "contentType": "model/mesh"
+        },
+        {
+          "byteSize": 3681640,
+          "name": "template_t1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Infant/infant-template/template_t1.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 13062,
+          "name": "template_L_atlas.gii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Infant/infant-template/template_L_atlas.gii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 803983,
+          "name": "template_R.gii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Infant/infant-template/template_R.gii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 12958,
+          "name": "template_R_atlas.gii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Infant/infant-template/template_R_atlas.gii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 602133,
+          "name": "template_R.mesh",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Infant/infant-template/template_R.mesh",
+          "contentType": "model/mesh"
+        },
+        {
+          "byteSize": 3681640,
+          "name": "template_t2.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Infant/infant-template/template_t2.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 604125,
+          "name": "template_L.mesh",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Infant/infant-template/template_L.mesh",
+          "contentType": "model/mesh"
+        }
+      ],
+      "contributors": [
+        "Kabdebon, C.",
+        "Dehaene-Lambertz, Ghislaine",
+        "Dubois, Jessica",
+        "Perrot, M.",
+        "Simmonet, H.",
+        "Leroy, Francois"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Anatomical correlations of the international 10–20 sensor placement system in infants",
+          "cite": "Kabdebon, C., Leroy, F., Simmonet, H., Perrot, M., Dubois, J., & Dehaene-Lambertz, G. (2014). Anatomical correlations of the international 10–20 sensor placement system in infants. NeuroImage, 99, 342–356. ",
+          "doi": "10.1016/j.neuroimage.2014.05.046"
+        }
+      ]
+    },
+    {
+      "formats": [
+        ".mhd",
+        ".raw",
+        " image/nii;version=0"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "Waxholm Space rat brain atlas v.2.0"
+        }
+      ],
+      "custodians": [
+        "Axer, Markus"
+      ],
+      "description": "The 3D fibre orientation model of a Wistar rat brain was derived from 3D-Polarized Light Imaging (3D-PLI) as described in Axer et al. (2011a). \\r\\nThe Wistar rat brain was immersion fixed in 4% paraformaldehyde. After cryoprotection (20% glycerin), the brain was deep frozen at -70°C and stored till further processing. The brain was serially sectioned in the coronal plane (section thickness 60 µm) using a large-scale cryostat microtome (Polycut CM 3500, Leica, Germany) and coverslipped with glycerin. Immediately after coverslipping, the sections were measured using the large-area polarimeter (LAP, pixel size: 64 µm x 64 µm, cf. Axer, 2011a). During sectioning, each blockface was digitized using a CCD camera mounted above the brain in order to obtain an undistorted reference image of each section. No staining was applied. This procedure resulted in an uninterrupted series of sections through the entire brain, which ultimately enabled the 3D reconstruction.\\r\\nThe application of the Jones calculus [Jones, 1941] describes the light transmittance through the LAP and enables the calculation of the individual spatial fiber orientation in each voxel (defined by pixel size and section thickness). The fiber orientation is defined by the pair of angles (α, ϕ) = (inclination, direction) indicating the fiber axis orientation out of and within the section plane, respectively. Inclination and direction angles are encoded in HSV color space to provide one fiber orientation map (FOM) per section. The entire data set of aligned FOMs (i.e. the fibre orientation model) is assembled in a single NIfTI file (http://nifti.nimh.nih.gov).\\r\\n3D reconstruction of the FOMs was done in a sequential application of affine and b-spline based image alignment steps with the reconstructed blockface volume acting as reference brain. Afterwards the fibre orientation model was transferred into the common rodent reference space, the Waxholm Space atlas [Papp et al., 2014]. The transformation of the brains into the same space was done in two steps: (i) a 3D affine registration ensured the correct spatial alignment of the brains and (ii) a subsequent 3D non-linear registration compensated non-linear distortions of the brain sections.\\r\\nThe fibre orientation model of the rat brain is not part of the proposed deliverables, but it is of utmost relevance for cross-SPs data integration and platform developments.\\r\\nThe application of polarization microscopy to unstained sections of brain tissue has been extensively described in peer-reviewed publications (e.g., Axer et al. 2011a,b, Larsen et al. 2007, Wiese et al. 2014). The 3D reconstruction of histological sections based on a blockface reference has been demonstrated by Palm et al. (2010). The Waxholm Space atlas [Papp et al. (2014)] defines the reference space for rodents in the HBP and it consists of high resolution, contrast enhanced structural (including T2 and T2*-weighted) and diffusion weighted MR images with 39 μm isotropic voxels for the MRI volume and 78 μm isotropic voxels for the DTI volume. In total 79 major anatomical structures were delineated based on the architectural details in both gray and white matter, demonstrated by the structural images.\\r\\nThe dataset comprises the following files:\\r\\n1.\\tR2022_reco_blockface.nii: reconstructed blockface volume\\r\\n2.\\tR2022_reco_foms.nii: reconstructed fiber orientation maps\\r\\n3.\\tWHS_MRI_toR2022.nii: WHS MRI volume aligned to R2022_reco_blockface.nii\\r\\n4.\\tWHS_atlas_toR2022.nii: WHS atlas template aligned to R2022_reco_blockface.nii",
+      "licenseInfo": [
+        "Creative Commons Attribution-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Wistar rat brain fibre orientation model",
+      "files": [],
+      "contributors": [
+        "Zilles, Karl",
+        "Bjaalie, Jan G.",
+        "Amunts, Katrin",
+        "Schubert, Nicole",
+        "Leergaard, Trygve B.",
+        "Huysegoms, Marcel",
+        "Huynh, Anh-Minh",
+        "Palomero-Gallagher, Nicola",
+        "Schober, Martin",
+        "Axer, Markus",
+        "Kirlangic, Mehmet E"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "3D Reconstructed Cyto-, Muscarinic M2 Receptor, and Fiber Architecture of the Rat Brain Registered to the Waxholm Space Atlas.",
+          "cite": "Schubert N, Axer M, Schober M, Huynh A-M, Huysegoms M, Palomero-Gallagher N, Bjaalie JG, Leergaard TB, Kirlangic ME, Amunts K and Zilles K (2016) 3D Reconstructed Cyto-, Muscarinic M2 Receptor, and Fiber Architecture of the Rat Brain Registered to the Waxholm Space Atlas. Front. Neuroanat. 10:51. doi: 10.3389/fnana.2016.00051",
+          "doi": "10.3389/fnana.2016.00051"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Jankowsky, Joanna L."
+      ],
+      "description": "Bright-field microscopy images of serial coronal brain sections showing Purkinje cell protein 2 (Pcp2) promoter expression in a bigenic Pcp2-tetracycline-transactivator (tTA) mouse brain (case 4340, adult male), generated using a driver-reporter construct in which the Pcp2-tTA promoter regulates the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, which is visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Our data confirm earlier reports that Pcp2-tTA promoter expression is restricted to cerebellar Purkinje cells.",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Purkinje cell protein 2 tetracycline-transactivator expression: coronal sections (case 4340)",
+      "files": [],
+      "contributors": [
+        "Bjaalie, Jan G.",
+        "Puchades, Maja A.",
+        "Yetman, Michael J.",
+        "Jankowsky, Joanna L.",
+        "Lillehaug, Sveinung",
+        "Leergaard, Trygve B.",
+        "Checinska, Martyna M."
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+      "description": "This dataset contains the distinct architectonic Area 45 (IFG) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Area 45 (IFG). The probability map of Area 45 (IFG) is given in file jubrain-pmap-v22c_space-mnicolin27_ Area-45.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
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+        "Free"
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+        {
+          "name": "Area 45 (IFG)"
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+      ],
+      "contributors": [
+        "Eickhoff, Simon B.",
+        "Shah, Nadim J.",
+        "Zilles, Karl",
+        "Weiss, Peter H.",
+        "Marshall, John C.",
+        "Bürgel, Uli",
+        "Amunts, Katrin",
+        "Gurd, Jennifer M.",
+        "Fink, Gereon R.",
+        "Pieperhoff, P.",
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Uylings, Harry B.M."
+      ],
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+        "10.25493/J2KZ-AZW"
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+          "name": "Analysis of neural mechanisms underlying verbal fluency in cytoarchitectonically defined stereotaxic space—The roles of Brodmann areas 44 and 45",
+          "cite": "Amunts, K., Weiss, P. H., Mohlberg, H., Pieperhoff, P., Eickhoff, S., Gurd, J. M., … Zilles, K. (2004). Analysis of neural mechanisms underlying verbal fluency in cytoarchitectonically defined stereotaxic space—The roles of Brodmann areas 44 and 45. NeuroImage, 22(1), 42–56. ",
+          "doi": "10.1016/j.neuroimage.2003.12.031"
+        },
+        {
+          "name": "Broca's region revisited: Cytoarchitecture and intersubject variability",
+          "cite": "Amunts, K., Schleicher, A., Bürgel, U., Mohlberg, H., Uylings, H. B. M., & Zilles, K. (1999). Broca’s region revisited: Cytoarchitecture and intersubject variability. The Journal of Comparative Neurology, 412(2), 319–341. ",
+          "doi": "10.1002/(SICI)1096-9861(19990920)412:2<319::AID-CNE10>3.0.CO;2-7"
+        }
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+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
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+      "name": "Spike time dependent plasticity (STDP) data from neonate C57BL/6 (wild-type) mice, negative pairing",
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+        "Cherubini, Enrico",
+        "Marchetti, Cristina"
+      ],
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+        "10.25493/G3W4-X3P"
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+        "NIFTI"
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+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
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+        "Free"
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+      "name": "Probabilistic cytoarchitectonic map of Area 6d2 (PreG)",
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+      "contributors": [
+        "Sigl, Benjamin",
+        "Amunts, Katrin",
+        "Eickhoff, Simon B.",
+        "Mohlberg, Hartmut",
+        "Bludau, Sebastian",
+        "Caspers, Svenja"
+      ],
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+      "publications": []
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+      "custodians": [
+        "Poupon, Cyril"
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+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
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+        "Free"
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+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
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+        }
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+    },
+    {
+      "formats": [
+        "NIFTI"
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+      "custodians": [
+        "Poupon, Cyril"
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+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_IP-SP_0.nii",
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+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area Fp2 (Fpole) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Area Fp2 (Fpole). The probability map of Area Fp2 (Fpole) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-Fp2.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area Fp2 (Fpole)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area Fp2 (Fpole)",
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Bludau, Sebastian",
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Fox, P.T.",
+        "Laird, A.R.",
+        "Caspers, S.",
+        "Mohlberg, Hartmut",
+        "Eickhoff, Simon B."
+      ],
+      "kgReference": [
+        "10.25493/26WT-E3P"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitecture, probability maps and functions of the human frontal pole",
+          "cite": "Bludau, S., Eickhoff, S. B., Mohlberg, H., Caspers, S., Laird, A. R., Fox, P. T., … Amunts, K. (2014). Cytoarchitecture, probability maps and functions of the human frontal pole. NeuroImage, 93, 260–275. ",
+          "doi": "10.1016/j.neuroimage.2013.05.052"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Pars Triangularis and Insula gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_Tr-Ins_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_Tr-Ins_0",
+      "files": [
+        {
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+          "name": "rh_Tr-Ins_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_Tr-Ins_0.nii",
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+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
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+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
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+          "doi": "10.1016/j.neuroimage.2016.11.066"
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+      ]
+    },
+    {
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+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
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+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Inferior Parietal and Lateral Occipital gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
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+      "parcellationRegion": [
+        {
+          "name": "lh_IP-LO_1"
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+      ],
+      "name": "Probabilistic maps of lh_IP-LO_1",
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+          "contentType": "application/octet-stream"
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+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "TIFF"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Haug, Smejda",
+        "Mogens, Finn"
+      ],
+      "description": "",
+      "licenseInfo": [
+        "Creative Commons Attribution-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Whole brain"
+        }
+      ],
+      "name": "Waxholm Space rat brain reference atlas enriched with additional receptor data",
+      "files": [],
+      "contributors": [
+        "Mogens, Finn",
+        "Haug, Smejda"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Sulphide Silver Pattern and Cytoarchitectonics of Parahippocampal Areas in the Rat",
+          "cite": "",
+          "doi": "10.1007/9783642664489"
+        },
+        {
+          "name": "Heavy Metals in the Brain",
+          "cite": "",
+          "doi": "10.1007/978-3-642-51585-9"
+        },
+        {
+          "name": "Light microscopical mapping of the hippocampal region, the pyriform cortex and the corticomedial amygdaloid nuclei of the rat with Timm's sulphide silver method",
+          "cite": "",
+          "doi": "10.1007/bf00519123"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Modulation of GABAergic currents by anti-neuroligin 2 and anti-gephyrin intrabodies (delta2-188)",
+      "files": [],
+      "contributors": [
+        "Pizzarelli, Rocco",
+        "Cherubini, Enrico",
+        "Marinelli, Silvia",
+        "Pimpinella, Domenico"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Inferior Parietal and Middle Temporal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_IP-MT_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_IP-MT_0",
+      "files": [
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+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_IP-MT_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area PFt using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp\n\nkainate (glutamate; [³H]kainate): fp\n\nNMDA (glutamate; [³H]MK-801): fp\n\nmGluR2/3 (glutamate; [³H] LY 341 495): fp\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp\n\nα₁ (noradrenalin; [³H]prazosin): fp\n\nα₂ (noradrenalin; [³H]UK-14,304): fp\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp\n\n5-HT₂ (serotonin; [³H]ketanserin): fp\n\nD₁ (dopamine; [³H]SCH23390): fp\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area PFt"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area PFt",
+      "files": [
+        {
+          "byteSize": 44096,
+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        },
+        {
+          "byteSize": 16310,
+          "name": "PFt_fp_20180405.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_PFt/PFt_fp_20180405.xlsx",
+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Caspers, S.",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike"
+      ],
+      "kgReference": [
+        "10.25493/E7PM-FDC"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        },
+        {
+          "name": "Organization of the Human Inferior Parietal Lobule Based on Receptor Architectonics",
+          "cite": "Caspers, S., Schleicher, A., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Zilles, K. (2012). Organization of the Human Inferior Parietal Lobule Based on Receptor Architectonics. Cerebral Cortex, 23(3), 615–628. ",
+          "doi": "10.1093/cercor/bhs048"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "tif, nii"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Axer, Markus"
+      ],
+      "description": "Registration and curation of 3D-PLI data for selected anatomical structures into the atlas. The data will be registered to the Big Brain template.",
+      "licenseInfo": [],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Hippocampus"
+        }
+      ],
+      "name": "Human temporal lobe with hippocampus",
+      "files": [],
+      "contributors": [
+        "Axer, Markus"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area 3b (PostCG) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area 3b (PostCG). The probability map of Area 3b (PostCG) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-3b.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 3b (PostCG)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area 3b (PostCG)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-3b.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-3b.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Schormann, Thorsten",
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Geyer, Stefan"
+      ],
+      "kgReference": [
+        "10.25493/W4WS-B3P"
+      ],
+      "publications": [
+        {
+          "name": "Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex",
+          "cite": "Geyer, S., Schormann, T., Mohlberg, H., & Zilles, K. (2000). Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex. NeuroImage, 11(6), 684–696. ",
+          "doi": "10.1006/nimg.2000.0548"
+        },
+        {
+          "name": "Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex",
+          "cite": "Geyer, S., Schleicher, A., & Zilles, K. (1999). Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex. NeuroImage, 10(1), 63–83. ",
+          "doi": "10.1006/nimg.1999.0440"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Inferior Parietal and Middle Temporal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_IP-MT_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_IP-MT_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "lh_IP-MT_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_IP-MT_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Superior Temporal and Insula gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_ST-Ins_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_ST-Ins_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "lh_ST-Ins_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_ST-Ins_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic DG (Hippocampus) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to DG (Hippocampus). The probability map of DG (Hippocampus) is given in file jubrain-pmap-v22c_space-mnicolin27_Hippocampus-DG.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "DG (Hippocampus)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of DG (Hippocampus)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Hippocampus-DG.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Hippocampus-DG.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Habel, U.",
+        "Zilles, Karl",
+        "Schneider, F.",
+        "Shah, Nadim J.",
+        "Mohlberg, Hartmut",
+        "Pieperhoff, P.",
+        "Kindler, M.",
+        "Kedo, O.",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [
+        "10.25493/1KV8-B9G"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps",
+          "cite": "Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N. J., … Zilles, K. (2005). Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and Embryology, 210(5-6), 343–352. ",
+          "doi": "10.1007/s00429-005-0025-5"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "nifti, mnc"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Evans, Alan C.",
+        "Amunts, Katrin"
+      ],
+      "description": "BigBrain is a ultrahigh-resolution three-dimensional (3D) model of a human brain at nearly cellular resolution of 20 micrometers, based on the reconstruction of 7404 histological sections. This dataset contains the volumes in different template spaces: The original Big Brain histological space, which corresponds to the 2D section release, as well as the MNI ICBM152 and ADNI coordinate systems. In addition, the final aligned sections in the coronal, axial and sagittal dimension are also available.\n- Dataset \"[BigBrain High-resolution whole brain model: 2D Sections/Coronal](https://www.humanbrainproject.eu/en/explore-the-brain/search/#Dataset/1f50424206be7a0c1b8379bf8817be5e)\"\n- Dataset \"[BigBrain High-resolution whole brain model: 2D Sections/Axial](https://www.humanbrainproject.eu/en/explore-the-brain/search/#Dataset/c051f7cb18b7c998d815fcb71ed6b5d7)\"\n- Dataset \"[BigBrain High-resolution whole brain model: 2D Sections/Sagittal](https://www.humanbrainproject.eu/en/explore-the-brain/search/#Dataset/9e36fc587ce8193795137371a85a351e)\"",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "BigBrain High-resolution whole brain model: Downscaled volumes in minc and NIfTI format",
+      "files": [],
+      "contributors": [
+        "Amunts, Katrin",
+        "Evans, Alan C.",
+        "Zilles, Karl",
+        "Lippert, T.",
+        "Shah, Nadim J.",
+        "Oros-Peusquens, Ana-Maria",
+        "Lewis, Lindsay B.",
+        "Bazin, P.-L.",
+        "Bludau, Sebastian",
+        "Rousseau, M.-E.",
+        "Dickscheid, Timo",
+        "Mohlberg, Hartmut",
+        "Borgeat, L.",
+        "Lepage, Claude"
+      ],
+      "kgReference": [
+        "10.1126/science.1235381"
+      ],
+      "publications": [
+        {
+          "name": "BigBrain: An Ultrahigh-Resolution 3D Human Brain Model",
+          "cite": "Amunts, K., Lepage, C., Borgeat, L., Mohlberg, H., Dickscheid, T., Rousseau, M.-E., … Evans, A. C. (2013). BigBrain: An Ultrahigh-Resolution 3D Human Brain Model. Science, 340(6139), 1472–1475. ",
+          "doi": "10.1126/science.1235381"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "Nifti Files, gifti files, csv files, json files"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Thirion, Bertrand"
+      ],
+      "description": "This dataset contains functional magnetic resonance images (fMRIs) of 12 subjects performing RSVP Language task to localize the areas implicated in language comprehension, participants were presented with stimuli consisting of sequences of words, pseudowords or nonwords. For some conditions, these sequences were composed by well-formed sentences. They were presented as visual stimuli, using a Rapid-Serial- Visual-Presentation (RSVP) paradigm. Concretely, there were six experimental conditions featuring the different types of stimuli: i) complex meaningful sentences, containing at least two clauses (e.g. a main and a relative clause); ii) simple meaningful sentences, with only one main clause; iii) jabberwocky, obtained from well-formed sentences whose content words were replaced by meaningless, yet pronounceable pseudowords; iv) lists of words; v) lists of pseudowords; and vi) list of non-words (aka consonantstrings). Following each sequence after a short delay, a probe (which could be a word, pseudoword or non-word) was displayed with a 50% probability of having been presented in the sequence. Participants had then to indicate, by pressing one of the two possible response buttons, whether the probe had appeared in the sentence. One session of data collection comprised six runs; each of them included sixty trials related to the six experimental conditions, i.e. ten trials corresponded to one condition. The order of the trials was pseudo-randomized within and between runs across participants, such that the same experimental condition did not occur in two immediately successive trials. A trial lasted ten seconds. It started with the display of a fixation cross for two seconds, followed by the display of a blank screen for 0.5 seconds. Afterwards, a sequence of ten stimuli was presented at a rate of one stimulus per 0.4 seconds. Further, a blank screen was displayed during a randomly varying period of time between one and 1.5 seconds, followed by the display of a fixation cross for 0.5 seconds plus a probe stimulus for 0.5 seconds. Finally, the stimuli were cleared and a response-time window opened for 2 seconds.\n\n[https://openfmri.org/dataset/ds000244/](https://openfmri.org/dataset/ds000244/)\n\n[https://neurovault.org/collections/2138/](https://neurovault.org/collections/2138/)",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
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+          "contentType": "application/octet-stream"
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+      ],
+      "contributors": [
+        "Pinho, Ana Luísa",
+        "Thirion, Bertrand",
+        "Hertz-Pannier, Lucie",
+        "Dehaene, Stanislas",
+        "Pallier, Christophe",
+        "Varoquaux, Gaël",
+        "Eger, Evelyn",
+        "Pinel, Philippe",
+        "Martins, Bernadette",
+        "Doublé, Christine",
+        "Médiouni-Cloarec, Gaëlle",
+        "Joly-Testault, Véronique",
+        "Laurier, Laurence",
+        "Roger, Séverine",
+        "Becuwe-Desmidt, Séverine",
+        "Ginisty, Chantal",
+        "Denghien, Isabelle",
+        "Dohmatob, Elvis",
+        "Fabre, Murielle",
+        "Ruest, Torsten",
+        "Amadon, Alexis"
+      ],
+      "kgReference": [
+        "10.25493/PD28-TRA"
+      ],
+      "publications": [
+        {
+          "name": "Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping",
+          "cite": "Pinho, A. L., Amadon, A., Ruest, T., Fabre, M., Dohmatob, E., Denghien, I., … Thirion, B. (2018). Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping. Scientific Data, 5, 180105. ",
+          "doi": "10.1038/sdata.2018.105"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area Te2 using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp\n\nkainate (glutamate; [³H]kainate): fp\n\nNMDA (glutamate; [³H]MK-801): fp\n\nmGluR2/3 (glutamate; [³H] LY 341 495): fp\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp\n\nα₁ (noradrenalin; [³H]prazosin): fp\n\nα₂ (noradrenalin; [³H]UK-14,304): fp\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp\n\n5-HT₂ (serotonin; [³H]ketanserin): fp\n\nD₁ (dopamine; [³H]SCH23390): fp\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387\n\n\nThe receptor density data of this area were also published in:\n\nMorosan P, Rademacher J, Palomero-Gallagher N, and Zilles K (2005) Anatomical organization of the human auditory cortex: Cytoarchitecture and transmitter receptors. In Heil P, Scheich H, Bundinger E, and König R (Eds), The Auditory Cortex - Towards a Synthesis of Human and Animal Research. (pp. 27-50) [Mahwah, New Jersey, USA: Lawrence Erlbaum Associates](https://www.taylorfrancis.com/books/e/9781135613365/chapters/10.4324%2F9781410613066-9)",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area Te2"
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+      ],
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
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+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        }
+      ],
+      "contributors": [
+        "Friederici, Angela D.",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike",
+        "Morosan, Patricia",
+        "Rademacher, Jörg",
+        "Amunts, Katrin",
+        "Zilles, Karl"
+      ],
+      "kgReference": [
+        "10.25493/C279-428"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Lateral Orbitofrontal and Middle Orbitofrontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_LOF-MOF_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_LOF-MOF_0",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "rh_LOF-MOF_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_LOF-MOF_0.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "Nifti, Csv, Txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Thirion, Bertrand"
+      ],
+      "description": "#Title\nARCHI fMRI Database: spatial mapping paradigmm\n##Summarm\nThis dataset contains functional magnetic resonance images (fMRIs) of 77 subjects performing different tasks of a spatial mapping paradigm: 1) grasping versus orientation judgement, 2) left/right hand versus hand side, and 3) effect of ocular saccades. The tasks were executed in a (small) block design (5-7s each) with acquisition duration of  516s.\nVisual stimuli were displayed in four 250-ms epochs, separated by 100ms intervals (i.e., 1.3s in total). Auditory stimuli were drawn from a recorded male voice (i.e., a total of 1.6s for motor instructions, 1.2-1.7s for sentences, and 1.2-1.3s for subtraction). The auditory or visual stimuli were shown to the participants for passive viewing or button response in event-related paradigms. Post-scan questions verified that the experimental tasks were understood and followed correctly. \nWhole-brain EPI data were acquired with the same Siemens Trio with a 32 channel head coil (TR=2400ms, TE=30ms, flip angle=60°, in-plane FOV= 19.2 * 19.2 cm, 40 slices, 3.0mm isotropic voxels). A posterior-anterior phase encoding scheme was used for all images. Standard preprocessing was performed with SPM, including slice timing, motion correction, alignment, and spatial normalization.",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "ARCHI fMRI Database: spatial mapping paradigmm",
+      "files": [],
+      "contributors": [
+        "Thirion, Bertrand",
+        "Pinel, Philippe",
+        "Poupon, Cyril",
+        "Grisel, Olivier",
+        "Varoquaux, Gaël"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Principal Component Regression Predicts Functional Responses across Individuals",
+          "cite": "Thirion, B., Varoquaux, G., Grisel, O., Poupon, C., & Pinel, P. (2014). Principal Component Regression Predicts Functional Responses across Individuals. Lecture Notes in Computer Science, 741–748. ",
+          "doi": "10.1007/978-3-319-10470-6_92"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area hIP3 (IPS) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area hIP3 (IPS). The probability map of Area hIP3 (IPS) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-hIP3.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area hIP3 (IPS)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area hIP3 (IPS)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-hIP3.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-hIP3.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Eickhoff, Simon B.",
+        "Zilles, Karl",
+        "Hoemke, L.",
+        "Schleicher, Axel",
+        "Amunts, Katrin",
+        "Mohlberg, Hartmut",
+        "Scheperjans, Filip",
+        "Hermann, K."
+      ],
+      "kgReference": [
+        "10.25493/J9T6-TX9"
+      ],
+      "publications": [
+        {
+          "name": "Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Hermann, K., Eickhoff, S. B., Amunts, K., Schleicher, A., & Zilles, K. (2007). Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex. Cerebral Cortex, 18(4), 846–867. ",
+          "doi": "10.1093/cercor/bhm116"
+        },
+        {
+          "name": "Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Eickhoff, S. B., Hoemke, L., Mohlberg, H., Hermann, K., Amunts, K., & Zilles, K. (2008). Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex. Cerebral Cortex, 18(9), 2141–2157. ",
+          "doi": "10.1093/cercor/bhm241"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area PFcm using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp\n\nkainate (glutamate; [³H]kainate): fp\n\nNMDA (glutamate; [³H]MK-801): fp\n\nmGluR2/3 (glutamate; [³H] LY 341 495): fp\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp, pr, ar\n\nα₁ (noradrenalin; [³H]prazosin): fp\n\nα₂ (noradrenalin; [³H]UK-14,304): fp\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp\n\n5-HT₂ (serotonin; [³H]ketanserin): fp\n\nD₁ (dopamine; [³H]SCH23390): fp\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area PFcm"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area PFcm",
+      "files": [
+        {
+          "byteSize": 44096,
+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
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+        {
+          "byteSize": 15989,
+          "name": "PFcm_fp_20180405.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_PFcm/PFcm_fp_20180405.xlsx",
+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Caspers, S.",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike"
+      ],
+      "kgReference": [
+        "10.25493/5QDP-ARH"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        },
+        {
+          "name": "Organization of the Human Inferior Parietal Lobule Based on Receptor Architectonics",
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+        "Bizzi, Albero",
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+        "Alexander, Daniel C.",
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+        "Amunts, Katrin",
+        "Armstrong, E.",
+        "Fink, Gereon R.",
+        "Schleicher, Axel",
+        "Mohlberg, Hartmut",
+        "Zilles, Karl"
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+          "doi": "10.1002/cne.20849"
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+      "custodians": [
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+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Inferior Parietal and Inferior Temporal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
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+        "Mangin, Jean-François",
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+        "Duclap, Delphine",
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+        "Eickhoff, Simon B.",
+        "Hoemke, L.",
+        "Schleicher, Axel",
+        "Zilles, Karl",
+        "Mohlberg, Hartmut",
+        "Amunts, Katrin",
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+          "doi": "10.1093/cercor/bhm116"
+        },
+        {
+          "name": "Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Eickhoff, S. B., Hoemke, L., Mohlberg, H., Hermann, K., Amunts, K., & Zilles, K. (2008). Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex. Cerebral Cortex, 18(9), 2141–2157. ",
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+          "name": "MNI Colin 27"
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+      "custodians": [
+        "Amunts, Katrin"
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+      "description": "This dataset contains the distinct architectonic HATA (Hippocampus) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to HATA (Hippocampus). The probability map of HATA (Hippocampus) is given in file jubrain-pmap-v22c_space-mnicolin27_Hippocampus-HATA.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
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+        "Zilles, Karl",
+        "Schneider, F.",
+        "Habel, U.",
+        "Mohlberg, Hartmut",
+        "Pieperhoff, P.",
+        "Kindler, M.",
+        "Kedo, O.",
+        "Amunts, Katrin"
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+          "name": "Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps",
+          "cite": "Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N. J., … Zilles, K. (2005). Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and Embryology, 210(5-6), 343–352. ",
+          "doi": "10.1007/s00429-005-0025-5"
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+        "Schleicher, Axel",
+        "Zilles, Karl",
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+        "Caspers, S.",
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+        {
+          "name": "The human inferior parietal lobule in stereotaxic space",
+          "cite": "Caspers, S., Eickhoff, S. B., Geyer, S., Scheperjans, F., Mohlberg, H., Zilles, K., & Amunts, K. (2008). The human inferior parietal lobule in stereotaxic space. Brain Structure and Function, 212(6), 481–495. ",
+          "doi": "10.1007/s00429-008-0195-z"
+        },
+        {
+          "name": "The human inferior parietal cortex: Cytoarchitectonic parcellation and interindividual variability",
+          "cite": "Caspers, S., Geyer, S., Schleicher, A., Mohlberg, H., Amunts, K., & Zilles, K. (2006). The human inferior parietal cortex: Cytoarchitectonic parcellation and interindividual variability. NeuroImage, 33(2), 430–448. ",
+          "doi": "10.1016/j.neuroimage.2006.06.054"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area 9 using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp\n\nkainate (glutamate; [³H]kainate): fp\n\nNMDA (glutamate; [³H]MK-801): fp\n\nmGluR2/3 (glutamate; [³H] LY 341 495): fp\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp\n\nα₁ (noradrenalin; [³H]prazosin): fp\n\nα₂ (noradrenalin; [³H]UK-14,304): fp\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp\n\n5-HT₂ (serotonin; [³H]ketanserin): fp\n\nD₁ (dopamine; [³H]SCH23390): fp\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 9"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area 9",
+      "files": [
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+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        },
+        {
+          "byteSize": 16377,
+          "name": "9_fp_20180405.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_9/9_fp_20180405.xlsx",
+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike"
+      ],
+      "kgReference": [
+        "10.25493/97BA-87Y"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Superior Temporal and Transverse Temporal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_ST-TT_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_ST-TT_0",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "rh_ST-TT_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_ST-TT_0.nii",
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+        {
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+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Pars Triangularis and Insula gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_Tr-Ins_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_Tr-Ins_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "lh_Tr-Ins_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_Tr-Ins_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [
+        {
+          "name": "Allen adult mouse brain reference atlas V3"
+        }
+      ],
+      "custodians": [
+        "Ponting, Chris"
+      ],
+      "description": "These datasets report single cell transcriptomes from mouse hippocampus and cerebellum at P40 generated on the Fluidigm C1 modified running a script to implement Smart-seq2",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Single cell transcriptomes from mouse hippocampus and cerebellum generated on the Fluidigm C1 using Smart-seq2",
+      "files": [],
+      "contributors": [
+        "Oliver, Peter",
+        "Belgard, Grant",
+        "Ponting, Chris",
+        "Montiel, Juan"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area hOc4d (Cuneus) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area hOc4d (Cuneus). The probability map of Area hOc4d (Cuneus) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-hOc4d.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area hOc4d (Cuneus)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area hOc4d (Cuneus)",
+      "files": [
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-hOc4d.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-hOc4d.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Kujovic, Milenko",
+        "Amunts, Katrin",
+        "Eickhoff, Simon B.",
+        "Rottschy, Claudia",
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Malikovic, Aleksandar",
+        "Zilles, Karl"
+      ],
+      "kgReference": [
+        "10.25493/KQ4Y-Q4M"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonic mapping of the human dorsal extrastriate cortex",
+          "cite": "Kujovic, M., Zilles, K., Malikovic, A., Schleicher, A., Mohlberg, H., Rottschy, C., … Amunts, K. (2012). Cytoarchitectonic mapping of the human dorsal extrastriate cortex. Brain Structure and Function, 218(1), 157–172. ",
+          "doi": "10.1007/s00429-012-0390-9"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "D'Angelo, Egidio"
+      ],
+      "description": "Study and characterization of the synaptic properties of different cerebellar neuronal types.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Recordings of excitatory postsynaptic potentials from cerebellar neurons",
+      "files": [],
+      "contributors": [
+        "D'Angelo, Egidio",
+        "Prestori, Francesca",
+        "Locatelli, Francesca",
+        "Tognolina, Marialuisa"
+      ],
+      "kgReference": [
+        "10.25493/G07Q-K87"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "Nifti, Csv, Txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Thirion, Bertrand"
+      ],
+      "description": "This dataset contains functional magnetic resonance images (fMRIs) of 77 subjects performing different tasks of a  social paradigm: 1) speech versus non-speech sounds, 2) false belief- versus mechanistic kind of inference after visual or auditory presentation, 3) interacting versus non-interacting figures in the movie clip. The tasks were executed in a (small) block design (5-7s each) with acquisition duration of  489s.\nVisual stimuli were displayed in four 250-ms epochs, separated by 100ms intervals (i.e., 1.3s in total). Auditory stimuli were drawn from a recorded male voice (i.e., a total of 1.6s for motor instructions, 1.2-1.7s for sentences, and 1.2-1.3s for subtraction). The auditory or visual stimuli were shown to the participants for passive viewing or button response in event-related paradigms. Post-scan questions verified that the experimental tasks were understood and followed correctly. \nWhole-brain EPI data were acquired with the same Siemens Trio with a 32 channel head coil (TR=2400ms, TE=30ms, flip angle=60°, in-plane FOV= 19.2 * 19.2 cm, 40 slices, 3.0mm isotropic voxels). A posterior-anterior phase encoding scheme was used for all images. Standard preprocessing was performed with SPM, including slice timing, motion correction, alignment, and spatial normalization.",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "ARCHI fMRI Database: social paradigm",
+      "files": [],
+      "contributors": [
+        "Thirion, Bertrand",
+        "Pinel, Philippe",
+        "Poupon, Cyril",
+        "Grisel, Olivier",
+        "Varoquaux, Gaël"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Principal Component Regression Predicts Functional Responses across Individuals",
+          "cite": "Thirion, B., Varoquaux, G., Grisel, O., Poupon, C., & Pinel, P. (2014). Principal Component Regression Predicts Functional Responses across Individuals. Lecture Notes in Computer Science, 741–748. ",
+          "doi": "10.1007/978-3-319-10470-6_92"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic AStr (Amygdala) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to AStr (Amygdala). The probability map of AStr (Amygdala) is given in file jubrain-pmap-v22c_space-mnicolin27_Amygdala-AStr.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "AStr (Amygdala)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of AStr (Amygdala)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Amygdala-AStr.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Amygdala-AStr.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Shah, Nadim J.",
+        "Zilles, Karl",
+        "Schneider, F.",
+        "Habel, U.",
+        "Mohlberg, Hartmut",
+        "Pieperhoff, P.",
+        "Kindler, M.",
+        "Kedo, O.",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [
+        "10.25493/SH4V-6VC"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps",
+          "cite": "Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N. J., … Zilles, K. (2005). Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and Embryology, 210(5-6), 343–352. ",
+          "doi": "10.1007/s00429-005-0025-5"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "DeFelipe, Javier"
+      ],
+      "description": "This dataset contains the density of Chandelier (Ch) cell axon terminals  in various cytoarchitectonic areas of the human cerebral cortex. Cell density was analyzed on cell-body-stained histological sections of 3 human postmortem brains that were supplied by Dr R. Alcaraz, Forensic Pathology Service, Basque Institute of Legal Medicine, Bilbao, Spain.",
+      "licenseInfo": [],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Brodmann’s area 1"
+        },
+        {
+          "name": "Brodmann’s area 32"
+        },
+        {
+          "name": "Brodmann’s area 24"
+        },
+        {
+          "name": "Brodmann’s area 38"
+        },
+        {
+          "name": "Brodmann’s area 22"
+        },
+        {
+          "name": "Brodmann’s area 21"
+        },
+        {
+          "name": "Brodmann’s area 20"
+        },
+        {
+          "name": "Brodmann’s area 47"
+        },
+        {
+          "name": "Brodmann’s area 14"
+        },
+        {
+          "name": "Brodmann’s area 13"
+        },
+        {
+          "name": "Brodmann’s area 12"
+        },
+        {
+          "name": "Brodmann’s area 11"
+        },
+        {
+          "name": "Brodmann’s area 46"
+        },
+        {
+          "name": "Brodmann’s area 45"
+        },
+        {
+          "name": "Brodmann’s area 10"
+        },
+        {
+          "name": "Brodmann’s area 9"
+        },
+        {
+          "name": "Brodmann’s area 4"
+        },
+        {
+          "name": "Brodmann’s area 18"
+        },
+        {
+          "name": "Brodmann’s area 17"
+        },
+        {
+          "name": "Brodmann’s area 3b"
+        }
+      ],
+      "name": "Distribution and density of Chandelier cell axon terminals in the human cerebral cortex",
+      "files": [],
+      "contributors": [
+        "Inda, MC",
+        "Muñoz, A",
+        "DeFelipe, Javier"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "The Distribution of Chandelier Cell Axon Terminals that Express the GABA Plasma Membrane Transporter GAT-1 in the Human Neocortex",
+          "cite": "Inda, M., DeFelipe, J., & Muñoz, A. (2006). The Distribution of Chandelier Cell Axon Terminals that Express the GABA Plasma Membrane Transporter GAT-1 in the Human Neocortex. Cerebral Cortex, 17(9), 2060–2071. ",
+          "doi": "10.1093/cercor/bhl114"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Postcentral and Precentral gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_PoC-PrC_3"
+        }
+      ],
+      "name": "Probabilistic maps of lh_PoC-PrC_3",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "lh_PoC-PrC_3.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_PoC-PrC_3.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Rostral Anterior Cingulate and Superior Frontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_RAC-SF_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_RAC-SF_0",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "rh_RAC-SF_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_RAC-SF_0.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Postcentral and Precentral gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_PoC-PrC_1"
+        }
+      ],
+      "name": "Probabilistic maps of lh_PoC-PrC_1",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "lh_PoC-PrC_1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_PoC-PrC_1.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "A general procedure to fit individual synaptic events recorded from voltage clamp experiments was tested with various sets of experimental data on GABAergic synapses; gephyrin and gephyrin-dependent pathways were chosen as a suitable example of a kinetic model of synaptic transmission. The data used here are obtained from coronal hippocampal slices (300 μm thick) from juvenile (P21-30) C57B16/J male mice receiving input from parvalbumin positive (PV+) interneurons. The dataset contains 614 individual events recorded from 3 different neurons (expC1-C3). The first column of each txt file contains the time in ms and the other columns contain spontaneous inhibitory synaptic currents (sIPSCs) in pA.\nComputational modeling of brain circuits requires the definition of many parameters that are difficult to determine from experimental findings. One way to help interpret these data is to fit them using a particular kinetic model. In [1] we proposed a general procedure to fit individual synaptic events recorded from voltage clamp experiments. Starting from any given model description (mod file) in the NEURON simulation environment, the procedure exploits user-defined constraints, dependencies, and rules for the parameters of the model to fit the time course of individual spontaneous synaptic events that are recorded experimentally. A Python version is available for public use, as a Jupyter Notebook in the Collaboratory Portal of the Human Brain Project. To illustrate the potential application of the procedure, we tested its use with various sets of experimental data on GABAergic synapses; gephyrin and gephyrin-dependent pathways were chosen as a suitable example of a kinetic model of synaptic transmission. For individual spontaneous inhibitory events in hippocampal pyramidal CA1 neurons, we found that gephyrin-dependent subcellular pathways may shape synaptic events at different levels, and can be correlated with cell- or event-specific activity history and/or pathological conditions.\nFitting experimental data against a number of different models is a common way to do this (reviewed in [2]), and can help in the subsequent interpretation of the data. In general, experimental traces are fitted using specific approaches for specific purposes (e.g., [3], [4]). However, to the best of our knowledge, there is no easy, user-friendly, general procedure available for this purpose, especially in computational neuroscience. Our aim was thus to identify the appropriate conceptual structure of a procedure to obtain good, reliable fits of raw experimental traces of spontaneous synaptic events. This is an important step because spontaneous synaptic events have been so far exclusively analyzed using traces obtained by averaging many events. However, as can be easily imagined, each synapse in any given neuron has its own, independent, history of activation. The most likely physiological consequence is that the variables relative to the subcellular processes underlying synaptic transmission are different for each synapse. If a researcher is interested in testing a specific kinetic scheme implemented for specific biochemical pathways, the use of individual events is the most appropriate choice, since this approach would give information on the different combinations of model parameters that are consistent with the observed events. Averaging traces will lose a lot of relevant information.\nWe therefore present here the implementation of a procedure leading to the development of a unifying optimization method for individual synaptic events. Experimental data, kinetic models of synaptic transmission, and fitting parameters and their dependencies can be user defined/provided or gathered from databases. They can be used to generate optimized groups of parameters able to represent a population of synapses, either for simulation purposes or to study the functional consequences of a particular protein or subcellular synaptic transmission pathway. \n[1] Lupascu CA, Morabito A, Merenda E, et al. A General Procedure to Study Subcellular Models of Transsynaptic Signaling at Inhibitory Synapses. Frontiers in Neuroinformatics. 2016;10:23. doi:10.3389/fninf.2016.00023   \n[2] Van Geit W., De Schutter E., Achard P. (2008). Automated neuron model optimization techniques: a review. Biol. Cybern. 99, 241–251. 10.1007/s00422-008-0257-6  \n[3] Bekkers J. M. (2003). Convolution of mini distributions for fitting evoked synaptic amplitude histograms. J. Neurosci. Methods. 130, 105–114. 10.1016/j.jneumeth.2003.09.018  \n[4] Meisl G., Kirkegaard J. B., Arosio P., Michaels T. C., Vendruscolo M., Dobson C. M., et al. . (2016). Molecular mechanisms of protein aggregation from global fitting of kinetic models. Nat. Protoc. 11, 252–272. 10.1038/nprot.2016.010",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "sIPSCs from juvenile (P21-30) C57Bl6/J male mice from CA1 pyramidal neurons receiving input from PV+ interneurons",
+      "files": [],
+      "contributors": [
+        "Marchetti, Cristina",
+        "Marinelli, Silvia",
+        "Cherubini, Enrico"
+      ],
+      "kgReference": [
+        "10.25493/37YC-C88"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "png"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Evans, Alan C.",
+        "Amunts, Katrin"
+      ],
+      "description": "BigBrain is a ultrahigh-resolution three-dimensional (3D) model of a human brain at nearly cellular resolution of 20 micrometers, based on the reconstruction of 7404 histological sections. This dataset contains the reconstituted sections in the axial dimension. In addition, the final aligned sections in the coronal and sagittal dimension, and 3D histological volumes in histological space are also available.\n- Dataset \"[BigBrain High-resolution whole brain model: 2D Sections/Coronal](https://www.humanbrainproject.eu/en/explore-the-brain/search/#Dataset/1f50424206be7a0c1b8379bf8817be5e)\"\n- Dataset \"[BigBrain High-resolution whole brain model: 2D Sections/Sagittal](https://www.humanbrainproject.eu/en/explore-the-brain/search/#Dataset/9e36fc587ce8193795137371a85a351e)\"\n- Dataset \"[BigBrain High-resolution whole brain model: Downscaled volumes in minc and NIfTI format](https://www.humanbrainproject.eu/en/explore-the-brain/search/#Dataset/5cd7a689c75124a7455e1c31c9f478e0)\"",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "BigBrain High-resolution whole brain model: 2D Sections/Axial",
+      "files": [],
+      "contributors": [
+        "Amunts, Katrin",
+        "Evans, Alan C.",
+        "Zilles, Karl",
+        "Lippert, T.",
+        "Shah, Nadim J.",
+        "Oros-Peusquens, Ana-Maria",
+        "Lewis, Lindsay B.",
+        "Bazin, P.-L.",
+        "Bludau, Sebastian",
+        "Rousseau, M.-E.",
+        "Dickscheid, Timo",
+        "Mohlberg, Hartmut",
+        "Borgeat, L.",
+        "Lepage, Claude"
+      ],
+      "kgReference": [
+        "10.1126/science.1235381"
+      ],
+      "publications": [
+        {
+          "name": "BigBrain: An Ultrahigh-Resolution 3D Human Brain Model",
+          "cite": "Amunts, K., Lepage, C., Borgeat, L., Mohlberg, H., Dickscheid, T., Rousseau, M.-E., … Evans, A. C. (2013). BigBrain: An Ultrahigh-Resolution 3D Human Brain Model. Science, 340(6139), 1472–1475. ",
+          "doi": "10.1126/science.1235381"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Genon, Sarah"
+      ],
+      "description": "Five multimodal clusters were defined by examining convergence across parcellations based on task-based functional connectivity, resting-state functional connectivity and anatomical connectivity.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Caudal subregion of left dorsal premotor cortex"
+        },
+        {
+          "name": "Rostral middle subregion of left dorsal premotor cortex"
+        },
+        {
+          "name": "Rostral inferior subregion of left dorsal premotor cortex"
+        },
+        {
+          "name": "Intermediate ventral subregion of left dorsal premotor cortex"
+        },
+        {
+          "name": "Central subregion of left dorsal premotor cortex"
+        }
+      ],
+      "name": "Left PMd subregions defined across CBP modalities",
+      "files": [
+        {
+          "byteSize": 2023,
+          "name": "Conj_IntermediateVentral_yellow.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000773/Left PMdParcels/Conj_IntermediateVentral_yellow.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 2097,
+          "name": "Conj_RostralMiddle_red.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000773/Left PMdParcels/Conj_RostralMiddle_red.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 2068,
+          "name": "Conj_RostralInferior_Pink.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000773/Left PMdParcels/Conj_RostralInferior_Pink.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 2075,
+          "name": "Conj_Central_blue.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000773/Left PMdParcels/Conj_Central_blue.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 2149,
+          "name": "Conj_Caudal_green.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000773/Left PMdParcels/Conj_Caudal_green.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Genon, Sarah",
+        "Eickhoff, Simon B.",
+        "Amunts, Katrin",
+        "Jiang, Tianzi",
+        "Fox, P.T.",
+        "Laird, A.R.",
+        "Grefkes, Christian",
+        "Langner, Robert",
+        "Hoffstaedter, Felix",
+        "Cieslik, Edna C.",
+        "Müller, Veronika I.",
+        "Fan, Lingzhong",
+        "Li, Hai",
+        "Reid, Andrew T."
+      ],
+      "kgReference": [
+        "10.25493/C21W-ADY"
+      ],
+      "publications": [
+        {
+          "name": "The heterogeneity of the left dorsal premotor cortex evidenced by multimodal connectivity-based parcellation and functional characterization",
+          "cite": "Genon, S., Reid, A., Li, H., Fan, L., Müller, V. I., Cieslik, E. C., … Eickhoff, S. B. (2018). The heterogeneity of the left dorsal premotor cortex evidenced by multimodal connectivity-based parcellation and functional characterization. NeuroImage, 170, 400–411. ",
+          "doi": "10.1016/j.neuroimage.2017.02.034"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic CA1 (Hippocampus) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to CA1 (Hippocampus). The probability map of CA1 (Hippocampus) is given in file jubrain-pmap-v22c_space-mnicolin27_Hippocampus-CA1.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "CA1 (Hippocampus)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of CA1 (Hippocampus)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Hippocampus-CA1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Hippocampus-CA1.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Shah, Nadim J.",
+        "Zilles, Karl",
+        "Schneider, F.",
+        "Habel, U.",
+        "Mohlberg, Hartmut",
+        "Pieperhoff, P.",
+        "Kindler, M.",
+        "Kedo, O.",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [
+        "10.25493/W4WK-QSK"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps",
+          "cite": "Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N. J., … Zilles, K. (2005). Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and Embryology, 210(5-6), 343–352. ",
+          "doi": "10.1007/s00429-005-0025-5"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area 47 using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp, pr, ar\n\nkainate (glutamate; [³H]kainate): fp, pr, ar\n\nNMDA (glutamate; [³H]MK-801): fp, pr, ar\n\nmGluR2/3 (glutamate; [³H] LY 341 495): pr, ar\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp, pr, ar\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp, pr, ar\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp, pr, ar\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp, pr, ar\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp, pr, ar\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp, pr, ar\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp, pr, ar\n\nα₁ (noradrenalin; [³H]prazosin): fp, pr, ar\n\nα₂ (noradrenalin; [³H]UK-14,304): fp, pr, ar\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp, pr, ar\n\n5-HT₂ (serotonin; [³H]ketanserin): fp, pr, ar\n\nD₁ (dopamine; [³H]SCH23390): fp, pr, ar\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
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+      "name": "Density measurements of different receptors for Area 47",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
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+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike"
+      ],
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+        "10.25493/4M1R-KCP"
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+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        }
+      ]
+    },
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+        "NIFTI"
+      ],
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+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
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+      "description": "This dataset contains the distinct architectonic Area FG4 (FusG) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area FG4 (FusG). The probability map of Area FG4 (FusG) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-FG4.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area FG4 (FusG)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area FG4 (FusG)",
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Eickhoff, Simon B.",
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Grill-Spector, Kalanit",
+        "Bludau, Sebastian",
+        "Schleicher, Axel",
+        "Mohlberg, Hartmut",
+        "Caspers, Julian",
+        "Weiner, Kevin S.",
+        "Lorenz, Simon"
+      ],
+      "kgReference": [
+        "10.25493/6A73-MZS"
+      ],
+      "publications": [
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+          "name": "Two New Cytoarchitectonic Areas on the Human Mid-Fusiform Gyrus",
+          "cite": "Lorenz, S., Weiner, K. S., Caspers, J., Mohlberg, H., Schleicher, A., Bludau, S., … Amunts, K. (2015). Two New Cytoarchitectonic Areas on the Human Mid-Fusiform Gyrus. Cerebral Cortex, bhv225. ",
+          "doi": "10.1093/cercor/bhv225"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area opercularis 8 (OP8) in the frontal operculum. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area OP8. The probability map of Area OP8 is given in file jubrain-pmap-v22c_space-mnicolin27_Area-OP8.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
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+      "parcellationRegion": [
+        {
+          "name": "Area OP8"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area OP8",
+      "files": [],
+      "contributors": [
+        "Saal, Martin",
+        "Amunts, Katrin",
+        "Caspers, Svenja",
+        "Mohlberg, Hartmut",
+        "Bludau, Sebastian"
+      ],
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+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Caudal Middle Frontal and Pars Opercularis gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_CMF-Op_0"
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_CMF-Op_0.nii",
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+          "contentType": "application/octet-stream"
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+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
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+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
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+          "doi": "10.1016/j.neuroimage.2016.11.066"
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+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Lachaux, Jean-Philippe"
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+      "description": "The Human Intracranial Database (HID) is a collection of stereotactic electroencephalography (sEEG) data in 30 patients, each performing eight behavioral tasks. The behavioral tasks were used as functional localizers: short and classic task paradigms designed to activate large-scale neural networks involved in language processing (LEC1 and LEC2), verbal and visuo-spatial working memory (MVEB and MVIS), visual attention (VISU), motor behavior (MOTO), high-level visual (MCSE) and auditory perception (AUDI). Furthermore, patients were also recorded during resting state (REST). The sEEG data were obtained via several sEEG depth-electrodes (linear arrays with up to 20 contacts) that were implanted in each patient in a stereotactic surgery. Coordinates of the sEEG electrode contacts are provided in the individual brain space of each patient as well as in a reference brain space (MNI). Semantically sEEG electrode contacts were linked to brain areas of the MarsAtlas.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Human Intracranial Database (HID)",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Intracranial/intracranial.zip",
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+        }
+      ],
+      "contributors": [
+        "Jerbi, K.",
+        "Lachaux, Jean-Philippe",
+        "Berthoz, A.",
+        "Kahane, P.",
+        "Minotti, L.",
+        "Bertrand, O.",
+        "Ossandon, T.",
+        "Hamame, C. M.",
+        "Freyermuth, S.",
+        "Vidal, J. R."
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Long-Distance Amplitude Correlations in the High Gamma Band Reveal Segregation and Integration within the Reading Network",
+          "cite": "Vidal, J. R., Freyermuth, S., Jerbi, K., Hamame, C. M., Ossandon, T., Bertrand, O., … Lachaux, J.-P. (2012). Long-Distance Amplitude Correlations in the High Gamma Band Reveal Segregation and Integration within the Reading Network. Journal of Neuroscience, 32(19), 6421–6434. ",
+          "doi": "10.1523/JNEUROSCI.4363-11.2012"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic LB (Amygdala) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to LB (Amygdala). The probability map of LB (Amygdala) is given in file jubrain-pmap-v22c_space-mnicolin27_Amygdala-LB.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "LB (Amygdala)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of LB (Amygdala)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Amygdala-LB.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Amygdala-LB.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
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+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Habel, U.",
+        "Zilles, Karl",
+        "Schneider, F.",
+        "Shah, Nadim J.",
+        "Mohlberg, Hartmut",
+        "Pieperhoff, P.",
+        "Kindler, M.",
+        "Kedo, O.",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [
+        "10.25493/E7QC-B3Y"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps",
+          "cite": "Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N. J., … Zilles, K. (2005). Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and Embryology, 210(5-6), 343–352. ",
+          "doi": "10.1007/s00429-005-0025-5"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Posterior Cingulate and Precuneus gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_PoCi-PrCu_1"
+        }
+      ],
+      "name": "Probabilistic maps of lh_PoCi-PrCu_1",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
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+          "name": "lh_PoCi-PrCu_1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_PoCi-PrCu_1.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Superior Parietal and Supramarginal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_SP-SM_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_SP-SM_0",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "lh_SP-SM_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_SP-SM_0.nii",
+          "contentType": "application/octet-stream"
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "Spike-time dependent plasticity (STDP is a particular form of Hebbian type of learning which consists in bidirectional modifications of synaptic strength according to the temporal order of pre- and postsynaptic spiking (*Dan Y1, Poo MM (2006) Spike timing-dependent plasticity: from synapse to perception. Physiol Rev 86:1033-1048*). Thus, positively correlated pre- and postsynaptic spiking (pre before post) within a critical window leads to long term potentiation (LTP), whereas a negative correlation (post before pre) leads to long term depression (LTD).  \nAt the neonatal stage, the hippocampal mossy fiber (MF)-CA3 is GABAergic and exhibits STDP. Our data demonstrate that, at the same age, positive pairing fails to induce STD-LTP at MF-CA3 synapses in hippocampal slices obtained from neuroligin-3 (NL3) knock-in (NL3<sup>R451C</sup>KI) and NL3 knock-out (KO) mice. Similarly, in NLR<sup>R451C</sup> KI mice, negative pairing failed to cause STD-LTD. In contrast, STD-LTP and STD-LTD can be readily produced in control age-matched WT littermates. In NLR<sup>R451C</sup> KI  mice, the impairment in STD-LTP is maintained in adulthood when MF are glutamatergic. This set of data refers to the adult, neuroligin-3 knock-in mice, positive pairing condition.  \n\n**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Spike time dependent plasticity (STDP) data from adult neuroligin-3 knock-in mice, positive pairing",
+      "files": [],
+      "contributors": [
+        "Cherubini, Enrico",
+        "Marchetti, Cristina",
+        "Sgritta, Martina"
+      ],
+      "kgReference": [
+        "10.25493/J43Z-KH0"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [
+        {
+          "name": "Allen adult mouse brain reference atlas V3"
+        }
+      ],
+      "custodians": [
+        "Sylvestri, Ludovico"
+      ],
+      "description": "Whole-brain images of neuronal activation in mouse brain acquired with light-sheet microscopy. Animal models will be used to detect immediate early genes (IEGs) expression.",
+      "licenseInfo": [
+        "Creative Commons Attribution-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [
+        "Creative Commons Attribution-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "hbp-00931_RestImg_Dataset",
+      "files": [],
+      "contributors": [
+        "Franceschini,Alessandra",
+        "Di Giovanna,Antonino P.",
+        "Pavone, Francesco S.",
+        "Orsini, Francesco",
+        "Costantini, Irene",
+        "Mazzamuto,Giacomo",
+        "Silvestri, Ludovico",
+        "Muellenbroich,Marie C."
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
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+      "contributors": [
+        "Grefkes, Christian",
+        "Zilles, Karl",
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+        "Schormann, Thorsten",
+        "Geyer, Stefan"
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+      "contributors": [
+        "Habel, U.",
+        "Zilles, Karl",
+        "Schneider, F.",
+        "Shah, Nadim J.",
+        "Mohlberg, Hartmut",
+        "Pieperhoff, P.",
+        "Kindler, M.",
+        "Kedo, O.",
+        "Amunts, Katrin"
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+          "cite": "Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N. J., … Zilles, K. (2005). Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and Embryology, 210(5-6), 343–352. ",
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+        "Mohlberg, Hartmut",
+        "Zilles, Karl",
+        "Amunts, Katrin",
+        "Vogt, Brent A.",
+        "Schleicher, Axel",
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+        "Palomero-Gallagher, Nicola"
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+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Postcentral and Precentral gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
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+        "Guevara, Pamela",
+        "Mangin, Jean-François",
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+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
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+      "formats": [
+        "NIFTI"
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+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area PFcm (IPL) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area PFcm (IPL). The probability map of Area PFcm (IPL) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-PFcm.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
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+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Amunts, Katrin",
+        "Schleicher, Axel",
+        "Caspers, S.",
+        "Mohlberg, Hartmut",
+        "Scheperjans, Filip",
+        "Eickhoff, Simon B.",
+        "Geyer, Stefan"
+      ],
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+        "10.25493/G279-H6V"
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+          "name": "The human inferior parietal cortex: Cytoarchitectonic parcellation and interindividual variability",
+          "cite": "Caspers, S., Geyer, S., Schleicher, A., Mohlberg, H., Amunts, K., & Zilles, K. (2006). The human inferior parietal cortex: Cytoarchitectonic parcellation and interindividual variability. NeuroImage, 33(2), 430–448. ",
+          "doi": "10.1016/j.neuroimage.2006.06.054"
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+          "name": "The human inferior parietal lobule in stereotaxic space",
+          "cite": "Caspers, S., Eickhoff, S. B., Geyer, S., Scheperjans, F., Mohlberg, H., Zilles, K., & Amunts, K. (2008). The human inferior parietal lobule in stereotaxic space. Brain Structure and Function, 212(6), 481–495. ",
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+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Inferior Parietal and Supramarginal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
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+      "custodians": [
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+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Superior Parietal and Supramarginal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Caudal Middle Frontal and Postcentral gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_CMF-PoC_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_CMF-PoC_0",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "lh_CMF-PoC_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_CMF-PoC_0.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area 25 (sACC) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Area 25 (sACC). The probability map of Area 25 (sACC) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-25.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 25 (sACC)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area 25 (sACC)",
+      "files": [
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-25.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-25.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Mohlberg, Hartmut",
+        "Zilles, Karl",
+        "Amunts, Katrin",
+        "Vogt, Brent A.",
+        "Schleicher, Axel",
+        "Hoffstaedter, Felix",
+        "Eickhoff, Simon B.",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "kgReference": [
+        "10.25493/NMPJ-EU"
+      ],
+      "publications": [
+        {
+          "name": "Functional organization of human subgenual cortical areas: Relationship between architectonical segregation and connectional heterogeneity",
+          "cite": "Palomero-Gallagher, N., Eickhoff, S. B., Hoffstaedter, F., Schleicher, A., Mohlberg, H., Vogt, B. A., … Zilles, K. (2015). Functional organization of human subgenual cortical areas: Relationship between architectonical segregation and connectional heterogeneity. NeuroImage, 115, 177–190. ",
+          "doi": "10.1016/j.neuroimage.2015.04.053"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Marinelli, Silvia",
+        "Cherubini, Enrico"
+      ],
+      "description": "This dataset is temporarily under embargo. The data will become available for download after the embargo period",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Test doi: Modulation of GABAergic currents by anti-neuroligin 2 and anti-gephyrin intrabodies (scFvgephIsc cultures)",
+      "files": [],
+      "contributors": [
+        "Stendardo, Emiliana",
+        "Avvisati, Riccardo",
+        "Meringolo, Maria",
+        "Cherubini, Enrico",
+        "Malavasi, Elisa",
+        "Badiani, Aldo",
+        "Marinelli, Silvia"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Intravenous self-administration of benzydamine, a non-steroidal anti-inflammatory drug with a central cannabinoidergic mechanism of action",
+          "cite": "Avvisati, R., Meringolo, M., Stendardo, E., Malavasi, E., Marinelli, S., & Badiani, A. (2017). Intravenous self-administration of benzydamine, a non-steroidal anti-inflammatory drug with a central cannabinoidergic mechanism of action. Addiction Biology, 23(2), 610–619. ",
+          "doi": "10.1111/adb.12516"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "A general procedure to fit individual synaptic events recorded from voltage clamp experiments was tested with various sets of experimental data on GABAergic synapses; gephyrin and gephyrin-dependent pathways were chosen as a suitable example of a kinetic model of synaptic transmission. The data used here are obtained from coronal hippocampal slices (300 μm thick) from juvenile (P21-30) C57B16/J male mice and recorded from hippocampal CA1 pyramidal neurons receiving input from parvalbumin positive (PV+) and cholecystokinin positive (CCK+) interneurons. The dataset contains 2130 individual events recorded from 3 different neurons (expD1-D3). The first column of each txt file contains the time in ms and the other columns contain spontaneous inhibitory synaptic currents (sIPSCs) in pA.\nComputational modeling of brain circuits requires the definition of many parameters that are difficult to determine from experimental findings. One way to help interpret these data is to fit them using a particular kinetic model. In [1] we proposed a general procedure to fit individual synaptic events recorded from voltage clamp experiments. Starting from any given model description (mod file) in the NEURON simulation environment, the procedure exploits user-defined constraints, dependencies, and rules for the parameters of the model to fit the time course of individual spontaneous synaptic events that are recorded experimentally. A Python version is available for public use, as a Jupyter Notebook in the Collaboratory Portal of the Human Brain Project. To illustrate the potential application of the procedure, we tested its use with various sets of experimental data on GABAergic synapses; gephyrin and gephyrin-dependent pathways were chosen as a suitable example of a kinetic model of synaptic transmission. For individual spontaneous inhibitory events in hippocampal pyramidal CA1 neurons, we found that gephyrin-dependent subcellular pathways may shape synaptic events at different levels, and can be correlated with cell- or event-specific activity history and/or pathological conditions.\nFitting experimental data against a number of different models is a common way to do this (reviewed in [2]), and can help in the subsequent interpretation of the data. In general, experimental traces are fitted using specific approaches for specific purposes (e.g., [3], [4]). However, to the best of our knowledge, there is no easy, user-friendly, general procedure available for this purpose, especially in computational neuroscience. Our aim was thus to identify the appropriate conceptual structure of a procedure to obtain good, reliable fits of raw experimental traces of spontaneous synaptic events. This is an important step because spontaneous synaptic events have been so far exclusively analyzed using traces obtained by averaging many events. However, as can be easily imagined, each synapse in any given neuron has its own, independent, history of activation. The most likely physiological consequence is that the variables relative to the subcellular processes underlying synaptic transmission are different for each synapse. If a researcher is interested in testing a specific kinetic scheme implemented for specific biochemical pathways, the use of individual events is the most appropriate choice, since this approach would give information on the different combinations of model parameters that are consistent with the observed events. Averaging traces will lose a lot of relevant information.\nWe therefore present here the implementation of a procedure leading to the development of a unifying optimization method for individual synaptic events. Experimental data, kinetic models of synaptic transmission, and fitting parameters and their dependencies can be user defined/provided or gathered from databases. They can be used to generate optimized groups of parameters able to represent a population of synapses, either for simulation purposes or to study the functional consequences of a particular protein or subcellular synaptic transmission pathway. \n[1] Lupascu CA, Morabito A, Merenda E, et al. A General Procedure to Study Subcellular Models of Transsynaptic Signaling at Inhibitory Synapses. Frontiers in Neuroinformatics. 2016;10:23. doi:10.3389/fninf.2016.00023.  \n[2] Van Geit W., De Schutter E., Achard P. (2008). Automated neuron model optimization techniques: a review. Biol. Cybern. 99, 241–251. 10.1007/s00422-008-0257-6  \n[3] Bekkers J. M. (2003). Convolution of mini distributions for fitting evoked synaptic amplitude histograms. J. Neurosci. Methods. 130, 105–114. 10.1016/j.jneumeth.2003.09.018  \n[4] Meisl G., Kirkegaard J. B., Arosio P., Michaels T. C., Vendruscolo M., Dobson C. M., et al. . (2016). Molecular mechanisms of protein aggregation from global fitting of kinetic models. Nat. Protoc. 11, 252–272. 10.1038/nprot.2016.010",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "sIPSCs from juvenile (P21-30) C57B16/J male mice from hippocampal CA1 pyramidal neurons receiving input from PV+ and CCK+ interneurons",
+      "files": [],
+      "contributors": [
+        "Marinelli, Silvia",
+        "Marchetti, Cristina",
+        "Cherubini, Enrico"
+      ],
+      "kgReference": [
+        "10.25493/PHA7-5KZ"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area 7M (SPL) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area 7M (SPL). The probability map of Area 7M (SPL) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-7M.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 7M (SPL)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area 7M (SPL)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-7M.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-7M.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Hermann, K.",
+        "Scheperjans, Filip",
+        "Eickhoff, Simon B.",
+        "Hoemke, L.",
+        "Amunts, Katrin",
+        "Zilles, Karl"
+      ],
+      "kgReference": [
+        "10.25493/F26Z-16P"
+      ],
+      "publications": [
+        {
+          "name": "Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Hermann, K., Eickhoff, S. B., Amunts, K., Schleicher, A., & Zilles, K. (2007). Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex. Cerebral Cortex, 18(4), 846–867. ",
+          "doi": "10.1093/cercor/bhm116"
+        },
+        {
+          "name": "Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Eickhoff, S. B., Hoemke, L., Mohlberg, H., Hermann, K., Amunts, K., & Zilles, K. (2008). Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex. Cerebral Cortex, 18(9), 2141–2157. ",
+          "doi": "10.1093/cercor/bhm241"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area ifs2 (IFS) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area ifs2 (IFS). The probability map of  Area ifs2 (IFS) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-ifs2.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area ifs2 (IFS)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area ifs2 (IFS)",
+      "files": [],
+      "contributors": [
+        "Bradler, Sabine",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Caudal Anterior Cingulate gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_CAC-PoCi_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_CAC-PoCi_0",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "rh_CAC-PoCi_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_CAC-PoCi_0.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "Spike-time dependent plasticity (STDP is a particular form of Hebbian type of learning which consists in bidirectional modifications of synaptic strength according to the temporal order of pre- and postsynaptic spiking (*Dan Y1, Poo MM (2006) Spike timing-dependent plasticity: from synapse to perception. Physiol Rev 86:1033-1048*). Thus, positively correlated pre- and postsynaptic spiking (pre before post) within a critical window leads to long term potentiation (LTP), whereas a negative correlation (post before pre) leads to long term depression (LTD).  \nAt the neonatal stage, the hippocampal mossy fiber (MF)-CA3 is GABAergic and exhibits STDP. Our data demonstrate that, at the same age, positive pairing fails to induce STD-LTP at MF-CA3 synapses in hippocampal slices obtained from neuroligin-3 (NL3) knock-in (NL3<sup>R451C</sup> KI) and NL3 knock-out (KO) mice. Similarly, in NLR<sup>451C</sup> KI mice, negative pairing failed to cause STD-LTD. In contrast, STD-LTP and STD-LTD can be readily produced in control age-matched WT littermates. In NLR<sup>451C</sup> KI  mice, the impairment in STD-LTP is maintained in adulthood when MF are glutamatergic. This set of data refers to the neonate, NLR<sup>451C</sup> KI, positive pairing condition. \n\n**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Spike time dependent plasticity (STDP) data from neonate neuroligin-3 knock-in mice, positive pairing",
+      "files": [],
+      "contributors": [
+        "Sgritta, Martina",
+        "Marchetti, Cristina",
+        "Cherubini, Enrico"
+      ],
+      "kgReference": [
+        "10.25493/PF1P-YSE"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area Ig1 (Insula) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Area Ig1 (Insula). The probability map of Area Ig1 (Insula) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-Ig1.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area Ig1 (Insula)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area Ig1 (Insula)",
+      "files": [
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
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+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-Ig1.nii",
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+      "contributors": [
+        "Kurth, F.",
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Hoemke, L.",
+        "Schleicher, Axel",
+        "Eickhoff, Simon B."
+      ],
+      "kgReference": [
+        "10.25493/H2H6-0SA"
+      ],
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+          "name": "Cytoarchitecture and Probabilistic Maps of the Human Posterior Insular Cortex",
+          "cite": "Kurth, F., Eickhoff, S. B., Schleicher, A., Hoemke, L., Zilles, K., & Amunts, K. (2009). Cytoarchitecture and Probabilistic Maps of the Human Posterior Insular Cortex. Cerebral Cortex, 20(6), 1448–1461. ",
+          "doi": "10.1093/cercor/bhp208"
+        }
+      ]
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+        "Poupon, Cyril"
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+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_LOF-RMF_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_LOF-RMF_0",
+      "files": [
+        {
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Postcetnral and Supramarginal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
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+        "Free"
+      ],
+      "license": [],
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+          "name": "lh_PoC-SM_1"
+        }
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+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
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+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Caudal Middle Frontal and Precentral gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_CMF-PrC_1"
+        }
+      ],
+      "name": "Probabilistic maps of rh_CMF-PrC_1",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "rh_CMF-PrC_1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_CMF-PrC_1.nii",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in the Putamen using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp\n\nkainate (glutamate; [³H]kainate): fp\n\nNMDA (glutamate; [³H]MK-801): fp\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp\n\nα₁ (noradrenalin; [³H]prazosin): fp\n\nα₂ (noradrenalin; [³H]UK-14,304): fp\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp\n\n5-HT₂ (serotonin; [³H]ketanserin): fp\n\nD₁ (dopamine; [³H]SCH23390): fp\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Putamen"
+        }
+      ],
+      "name": "Density measurements of different receptors for Putamen ",
+      "files": [
+        {
+          "byteSize": 44096,
+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        },
+        {
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+          "name": "Pu_fp_20180405.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Nucleus_Pu/Pu_fp_20180405.xlsx",
+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        }
+      ],
+      "contributors": [
+        "Palomero-Gallagher, Nicola"
+      ],
+      "kgReference": [
+        "10.25493/4GZ1-SHH"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in the  Mediodorsal Thalamic nucleus using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp\n\nkainate (glutamate; [³H]kainate): fp\n\nNMDA (glutamate; [³H]MK-801): fp\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp\n\nα₁ (noradrenalin; [³H]prazosin): fp\n\nα₂ (noradrenalin; [³H]UK-14,304): fp\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp\n\n5-HT₂ (serotonin; [³H]ketanserin): fp\n\nD₁ (dopamine; [³H]SCH23390): fp\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Mediodorsal Thalamic nucleus"
+        }
+      ],
+      "name": "Density measurements of different receptors for Mediodorsal Thalamic nucleus",
+      "files": [
+        {
+          "byteSize": 15539,
+          "name": "MD_fp_20180405.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Nucleus_MD/MD_fp_20180405.xlsx",
+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
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+        {
+          "byteSize": 44096,
+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        }
+      ],
+      "contributors": [
+        "Palomero-Gallagher, Nicola"
+      ],
+      "kgReference": [
+        "10.25493/GKY8-NZR"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Isthmus Cingulate and Precuneus gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_IC-PrCu_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_IC-PrCu_0",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "lh_IC-PrCu_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/left hemisphere/Probability_Maps/lh_IC-PrCu_0.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area 44 (IFG) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Area 44 (IFG). The probability map of Area 44 (IFG) is given in file jubrain-pmap-v22c_space-mnicolin27_ Area-44.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 44 (IFG)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area 44 (IFG)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-44.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-44.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Fink, Gereon R.",
+        "Uylings, Harry B.M.",
+        "Shah, Nadim J.",
+        "Schleicher, Axel",
+        "Zilles, Karl",
+        "Gurd, Jennifer M.",
+        "Amunts, Katrin",
+        "Mohlberg, Hartmut",
+        "Bürgel, Uli",
+        "Eickhoff, Simon B.",
+        "Marshall, John C.",
+        "Pieperhoff, P.",
+        "Weiss, Peter H."
+      ],
+      "kgReference": [
+        "10.25493/7T39-YKE"
+      ],
+      "publications": [
+        {
+          "name": "Analysis of neural mechanisms underlying verbal fluency in cytoarchitectonically defined stereotaxic space—The roles of Brodmann areas 44 and 45",
+          "cite": "Amunts, K., Weiss, P. H., Mohlberg, H., Pieperhoff, P., Eickhoff, S., Gurd, J. M., … Zilles, K. (2004). Analysis of neural mechanisms underlying verbal fluency in cytoarchitectonically defined stereotaxic space—The roles of Brodmann areas 44 and 45. NeuroImage, 22(1), 42–56. ",
+          "doi": "10.1016/j.neuroimage.2003.12.031"
+        },
+        {
+          "name": "Broca's region revisited: Cytoarchitecture and intersubject variability",
+          "cite": "Amunts, K., Schleicher, A., Bürgel, U., Mohlberg, H., Uylings, H. B. M., & Zilles, K. (1999). Broca’s region revisited: Cytoarchitecture and intersubject variability. The Journal of Comparative Neurology, 412(2), 319–341. ",
+          "doi": "10.1002/(SICI)1096-9861(19990920)412:2<319::AID-CNE10>3.0.CO;2-7"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area FG1 using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp, ar\n\nkainate (glutamate; [³H]kainate): fp, ar\n\nNMDA (glutamate; [³H]MK-801): fp, ar\n\nmGluR2/3 (glutamate; [³H] LY 341 495): ar\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp, ar\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp, ar\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp, ar\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp, ar\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp, ar\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp, ar\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp, ar\n\nα₁ (noradrenalin; [³H]prazosin): fp, ar\n\nα₂ (noradrenalin; [³H]UK-14,304): fp, ar\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp, ar\n\n5-HT₂ (serotonin; [³H]ketanserin): fp, ar\n\nD₁ (dopamine; [³H]SCH23390): fp, ar\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area FG1"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area FG1",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
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+          "contentType": "application/zip"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Caspers, S.",
+        "Caspers, Julian",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
+        "Palomero-Gallagher, Nicola",
+        "Bacha-Trams, Maraike"
+      ],
+      "kgReference": [
+        "10.25493/QN6K-CHN"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
+          "doi": "10.1016/j.cortex.2014.07.007"
+        },
+        {
+          "name": "Receptor architecture of visual areas in the face and word-form recognition region of the posterior fusiform gyrus",
+          "cite": "Caspers, J., Palomero-Gallagher, N., Caspers, S., Schleicher, A., Amunts, K., & Zilles, K. (2013). Receptor architecture of visual areas in the face and word-form recognition region of the posterior fusiform gyrus. Brain Structure and Function, 220(1), 205–219. ",
+          "doi": "10.1007/s00429-013-0646-z"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [
+        {
+          "name": "Allen adult mouse brain reference atlas V3"
+        }
+      ],
+      "custodians": [
+        "Pavone, Francesco S."
+      ],
+      "description": "Localization of activated cells (expressing immedate early gene Arc) in half mouse brain, normal caging.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Arc expression in resting state",
+      "files": [],
+      "contributors": [
+        "Silvestri, Ludovico",
+        "Pavone, Francesco S."
+      ],
+      "kgReference": [
+        "10.25493/MDRW-SWQ"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Clascá, Francisco"
+      ],
+      "description": "This dataset describes quantitatively the somatodendritic and axonal structure of individual thalamocortical projection neurons in the thalamic somatic and visual sensory nuclei. The cells in the dataset were labeled using state-of the art viral vectors able to drive massive levels of expression of marker proteins in a neuron after a single transfection event, leaving the rest of the brain unlabeled. This allows the unambiguous visualization /measurement of the entire axonal tree, no matter how large or complex. They are the first visualization of these cells ever reported in mice. Experiments were conducted in vivo in wildtype C57BL76 adult animals and have a low (<5%) success rate. Accurate labeling analysis is extremely labor-intensive, especially for large and widespread-axon cells. The present dataset may thus be viewed as a collection of “archetypal” reference specimens of these neuron populations. The accurate 3D data and measurement of axonal arborizations of thalamocortical neurons provide in this dataset will be re-usable by any scientist developing biologically-based models of local and long range brain circuitry.  \n**Embargo status:**\n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "3D reconstruction and measurement of individual thalamocortical projection neuron axons of somatosensory and visual thalamic nuclei",
+      "files": [],
+      "contributors": [
+        "Clascá, Francisco",
+        "Evangelio, Marian",
+        "Rubio, Mario",
+        "García-Amado, María",
+        "Porrero, César"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Subc (Hippocampus) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Subc (Hippocampus). The probability map of Subc (Hippocampus) is given in file  jubrain-pmap-v22c_space-mnicolin27_Hippocampus-Subc.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Subc (Hippocampus)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Subc (Hippocampus)",
+      "files": [
+        {
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+          "name": "jubrain-pmap-v22c_space-mnicolin27_Hippocampus-Subc.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Hippocampus-Subc.nii",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Habel, U.",
+        "Zilles, Karl",
+        "Schneider, F.",
+        "Shah, Nadim J.",
+        "Mohlberg, Hartmut",
+        "Pieperhoff, P.",
+        "Kindler, M.",
+        "Kedo, O.",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [
+        "10.25493/57EJ-01Z"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps",
+          "cite": "Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N. J., … Zilles, K. (2005). Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and Embryology, 210(5-6), 343–352. ",
+          "doi": "10.1007/s00429-005-0025-5"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Rostral Middle Frontal and Superior Frontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_RMF-SF_1"
+        }
+      ],
+      "name": "Probabilistic maps of rh_RMF-SF_1",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
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+        {
+          "byteSize": 68240520,
+          "name": "rh_RMF-SF_1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_RMF-SF_1.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Modulation of GABAergic currents by anti-neuroligin 2 and anti-gephyrin intrabodies (scFvNLG2-645)",
+      "files": [],
+      "contributors": [
+        "Cherubini, Enrico",
+        "Cattaneo, Antonino",
+        "Meli, Giovanni",
+        "Giustizieri, Michela",
+        "Morabito, Annunziato",
+        "Marinelli, Silvia"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area ifs3 (IFS) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area ifs3 (IFS). The probability map of  Area ifs3 (IFS) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-ifs3.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area ifs3 (IFS)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area ifs3 (IFS)",
+      "files": [],
+      "contributors": [
+        "Bradler, Sabine",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Postcentral and Supramarginal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_PoC-SM_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_PoC-SM_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "rh_PoC-SM_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_PoC-SM_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI",
+        "3D-TIFF"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area ifj2 (IFS/PreS) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area ifj2 (IFS/PreS). The probability map of  Area ifj2 (IFS/PreS) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-ifj2.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area ifj2  (IFS/PreS)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area ifj2  (IFS/PreS)",
+      "files": [],
+      "contributors": [
+        "Bradler, Sabine",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Modulation of GABAergic currents by anti-neuroligin 2 and anti-gephyrin intrabodies (scFvgephIsc)",
+      "files": [],
+      "contributors": [
+        "Giustizieri, Michela",
+        "Cattaneo, Antonino",
+        "Morabito, Annunziato",
+        "Cherubini, Enrico",
+        "Meli, Giovanni",
+        "Marinelli, Silvia"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Caudal Middle Frontal and Superior Frontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_CMF-SF_0"
+        }
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+      "name": "Probabilistic maps of rh_CMF-SF_0",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area TE 1.1 (HESCHL) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area TE 1.1 (HESCHL). The probability map of Area TE 1.1 (HESCHL) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-TE-11.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area TE 1.1 (HESCHL)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area TE 1.1 (HESCHL)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-TE-11.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-TE-11.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Schleicher, Axel",
+        "Rademacher, Jörg",
+        "Werner, C.",
+        "Schormann, Thorsten",
+        "Morosan, Patricia",
+        "Freund, H.-J.",
+        "Amunts, Katrin",
+        "Zilles, Karl"
+      ],
+      "kgReference": [
+        "10.25493/55TY-YS8"
+      ],
+      "publications": [
+        {
+          "name": "Probabilistic Mapping and Volume Measurement of Human Primary Auditory Cortex",
+          "cite": "Rademacher, J., Morosan, P., Schormann, T., Schleicher, A., Werner, C., Freund, H.-J., & Zilles, K. (2001). Probabilistic Mapping and Volume Measurement of Human Primary Auditory Cortex. NeuroImage, 13(4), 669–683. ",
+          "doi": "10.1006/nimg.2000.0714"
+        },
+        {
+          "name": "Human Primary Auditory Cortex: Cytoarchitectonic Subdivisions and Mapping into a Spatial Reference System",
+          "cite": "Morosan, P., Rademacher, J., Schleicher, A., Amunts, K., Schormann, T., & Zilles, K. (2001). Human Primary Auditory Cortex: Cytoarchitectonic Subdivisions and Mapping into a Spatial Reference System. NeuroImage, 13(4), 684–701. ",
+          "doi": "10.1006/nimg.2000.0715"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area PF (IPL) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area PF (IPL). The probability map of Area PF (IPL) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-PF.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area PF (IPL)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area PF (IPL)",
+      "files": [
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-PF.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-PF.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Amunts, Katrin",
+        "Scheperjans, Filip",
+        "Eickhoff, Simon B.",
+        "Caspers, S.",
+        "Schleicher, Axel",
+        "Zilles, Karl",
+        "Geyer, Stefan",
+        "Mohlberg, Hartmut"
+      ],
+      "kgReference": [
+        "10.25493/H0GN-SA8"
+      ],
+      "publications": [
+        {
+          "name": "The human inferior parietal cortex: Cytoarchitectonic parcellation and interindividual variability",
+          "cite": "Caspers, S., Geyer, S., Schleicher, A., Mohlberg, H., Amunts, K., & Zilles, K. (2006). The human inferior parietal cortex: Cytoarchitectonic parcellation and interindividual variability. NeuroImage, 33(2), 430–448. ",
+          "doi": "10.1016/j.neuroimage.2006.06.054"
+        },
+        {
+          "name": "The human inferior parietal lobule in stereotaxic space",
+          "cite": "Caspers, S., Eickhoff, S. B., Geyer, S., Scheperjans, F., Mohlberg, H., Zilles, K., & Amunts, K. (2008). The human inferior parietal lobule in stereotaxic space. Brain Structure and Function, 212(6), 481–495. ",
+          "doi": "10.1007/s00429-008-0195-z"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "Nifti, Csv, Txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Thirion, Bertrand"
+      ],
+      "description": "This dataset contains functional magnetic resonance images (fMRIs) of 77 subjects performing different tasks of a generic localizer paradigm: 1) left versus right hand button press, 2) horizontal versus vertical checkerboard, 3) auditory versus visual instructions, 4) computation versus simple reading, 5) motor tasks versus language and 6) math tasks. \nThe tasks were executed in a fast-event related design with acquisition duration of  307s.\nVisual stimuli were displayed in four 250-ms epochs, separated by 100ms intervals (i.e., 1.3s in total). Auditory stimuli were drawn from a recorded male voice (i.e., a total of 1.6s for motor instructions, 1.2-1.7s for sentences, and 1.2-1.3s for subtraction). The auditory or visual stimuli were shown to the participants for passive viewing or button response in event-related paradigms. Post-scan questions verified that the experimental tasks were understood and followed correctly. \nWhole-brain EPI data were acquired with the same Siemens Trio with a 32 channel head coil (TR=2400ms, TE=30ms, flip angle=60°, in-plane FOV= 19.2 * 19.2 cm, 40 slices, 3.0mm isotropic voxels). A posterior-anterior phase encoding scheme was used for all images. Standard preprocessing was performed with SPM, including slice timing, motion correction, alignment, and spatial normalization.",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "ARCHI fMRI Database: generic localizer paradigm",
+      "files": [],
+      "contributors": [
+        "Thirion, Bertrand",
+        "Pinel, Philippe",
+        "Poupon, Cyril",
+        "Grisel, Olivier",
+        "Varoquaux, Gaël"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Principal Component Regression Predicts Functional Responses across Individuals",
+          "cite": "Thirion, B., Varoquaux, G., Grisel, O., Poupon, C., & Pinel, P. (2014). Principal Component Regression Predicts Functional Responses across Individuals. Lecture Notes in Computer Science, 741–748. ",
+          "doi": "10.1007/978-3-319-10470-6_92"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Posterios Cingulate and Precuneus gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_PoCi-PrCu_1"
+        }
+      ],
+      "name": "Probabilistic maps of rh_PoCi-PrCu_1",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "rh_PoCi-PrCu_1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_PoCi-PrCu_1.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Postcentral and Precentral gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_PoC-PrC_1"
+        }
+      ],
+      "name": "Probabilistic maps of rh_PoC-PrC_1",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "rh_PoC-PrC_1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_PoC-PrC_1.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "Spike-time dependent plasticity (STDP is a particular form of Hebbian type of learning which consists in bidirectional modifications of synaptic strength according to the temporal order of pre- and postsynaptic spiking (*Dan Y1, Poo MM (2006) Spike timing-dependent plasticity: from synapse to perception. Physiol Rev 86:1033-1048*). Thus, positively correlated pre- and postsynaptic spiking (pre before post) within a critical window leads to long term potentiation (LTP), whereas a negative correlation (post before pre) leads to long term depression (LTD).  \nAt the neonatal stage, the hippocampal mossy fiber (MF)-CA3 is GABAergic and exhibits STDP. Our data demonstrate that, at the same age, positive pairing fails to induce STD-LTP at MF-CA3 synapses in hippocampal slices obtained from neuroligin-3 (NL3) knock-in (NL3<sup>R451C</sup>KI) and NL3 knock-out (KO) mice. Similarly, in NLR<sup>R451C</sup> KI mice, negative pairing failed to cause STD-LTD. In contrast, STD-LTP and STD-LTD can be readily produced in control age-matched WT littermates. In NLR<sup>R451C</sup> KI  mice, the impairment in STD-LTP is maintained in adulthood when MF are glutamatergic. This set of data refers to the neonate, NL3 knock-out, positive pairing condition. \n\n**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Spike time dependent plasticity (STDP) data from neonate neuroligin-3 knock-out mice, positive pairing",
+      "files": [],
+      "contributors": [
+        "Cherubini, Enrico",
+        "Sgritta, Martina",
+        "Marchetti, Cristina"
+      ],
+      "kgReference": [
+        "10.25493/BT52-9CT"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [],
+      "description": "",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Whole-cell recording and labelling of hippocampal neurons in vivo",
+      "files": [],
+      "contributors": [
+        "Freund, Tamas",
+        "Kali, Szabolcs",
+        "Varga, Viktor",
+        "Jelitai, Marta",
+        "Komlosi, Ferenc"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Jankowsky, Joanna L."
+      ],
+      "description": "Bright-field microscopy images of serial horizontal brain sections showing Pituitary homeobox 3 (Pitx3) promoter expression in a bigenic Pitx3-tetracycline-transactivator (tTA) mouse brain case (6513, adult male), using a driver-reporter construct in which the Pitx3-tTA promoter regulates the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, which is visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Our data show that the Pitx3-tTA promoter is spatially restricted to the substantia nigra, ventral tegmental area, and a few other regions.",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Pituitary homeobox 3 tetracycline-transactivator expression: horizontal sections (case 6513)",
+      "files": [],
+      "contributors": [
+        "Lillehaug, Sveinung",
+        "Bjaalie, Jan G.",
+        "Yetman, Michael J.",
+        "Checinska, Martyna M.",
+        "Puchades, Maja A.",
+        "Jankowsky, Joanna L.",
+        "Leergaard, Trygve B."
+      ],
+      "kgReference": [
+        "10.25493/1AH7-T1A"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Jankowsky, Joanna L."
+      ],
+      "description": "Bright-field microscopy images of serial coronal brain sections showing Purkinje cell protein 2 (Pcp2) promoter expression in a bigenic Pcp2-tetracycline-transactivator (tTA) mouse brain (case 1261, adult male), generated using a driver-reporter construct in which the Pcp2-tTA promoter regulates the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, which is visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Our data confirm earlier reports that Pcp2-tTA promoter expression is restricted to cerebellar Purkinje cells.",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Purkinje cell protein 2 tetracycline-transactivator expression: coronal sections (case 1261)",
+      "files": [],
+      "contributors": [
+        "Lillehaug, Sveinung",
+        "Puchades, Maja A.",
+        "Checinska, Martyna M.",
+        "Bjaalie, Jan G.",
+        "Jankowsky, Joanna L.",
+        "Yetman, Michael J.",
+        "Leergaard, Trygve B."
+      ],
+      "kgReference": [
+        "10.25493/A2EG-VPR"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in Area Te1 using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp\n\nkainate (glutamate; [³H]kainate): fp\n\nNMDA (glutamate; [³H]MK-801): fp\n\nmGluR2/3 (glutamate; [³H] LY 341 495): fp\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp\n\nα₁ (noradrenalin; [³H]prazosin): fp\n\nα₂ (noradrenalin; [³H]UK-14,304): fp\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp\n\n5-HT₂ (serotonin; [³H]ketanserin): fp\n\nD₁ (dopamine; [³H]SCH23390): fp\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387\n\n\nThe receptor density data of this area were also published in:\n\nMorosan P, Rademacher J, Palomero-Gallagher N, and Zilles K (2005) Anatomical organization of the human auditory cortex: Cytoarchitecture and transmitter receptors. In Heil P, Scheich H, Bundinger E, and König R (Eds), The Auditory Cortex - Towards a Synthesis of Human and Animal Research. (pp. 27-50) [Mahwah, New Jersey, USA: Lawrence Erlbaum Associates](https://www.taylorfrancis.com/books/e/9781135613365/chapters/10.4324%2F9781410613066-9)",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area Te1"
+        }
+      ],
+      "name": "Density measurements of different receptors for Area Te1",
+      "files": [
+        {
+          "byteSize": 44096,
+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        },
+        {
+          "byteSize": 16355,
+          "name": "Te1_fp_20180405.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Area_Te1/Te1_fp_20180405.xlsx",
+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        }
+      ],
+      "contributors": [
+        "Morosan, Patricia",
+        "Amunts, Katrin",
+        "Bacha-Trams, Maraike",
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola",
+        "Rademacher, Jörg",
+        "Friederici, Angela D."
+      ],
+      "kgReference": [
+        "10.25493/AHX0-9PU"
+      ],
+      "publications": [
+        {
+          "name": "Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints",
+          "cite": "Zilles, K., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Friederici, A. D. (2015). Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints. Cortex, 63, 79–89. ",
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+      "description": "This dataset contains functional magnetic resonance images (fMRIs) of 77 subjects performing different tasks of a generic localizer paradigm: 1) gender judgement versus no task on face image and expression, 2) truth-worthiness versus gender judgement and 3) baseline. The tasks were executed in a (small) block design (5-7s each) with acquisition duration of 436s.\nVisual stimuli were displayed in four 250-ms epochs, separated by 100ms intervals (i.e., 1.3s in total). Auditory stimuli were drawn from a recorded male voice (i.e., a total of 1.6s for motor instructions, 1.2-1.7s for sentences, and 1.2-1.3s for subtraction). The auditory or visual stimuli were shown to the participants for passive viewing or button response in event-related paradigms. Post-scan questions verified that the experimental tasks were understood and followed correctly. \nWhole-brain EPI data were acquired with the same Siemens Trio with a 32 channel head coil (TR=2400ms, TE=30ms, flip angle=60°, in-plane FOV= 19.2 * 19.2 cm, 40 slices, 3.0mm isotropic voxels). A posterior-anterior phase encoding scheme was used for all images. Standard preprocessing was performed with SPM, including slice timing, motion correction, alignment, and spatial normalization.",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "ARCHI fMRI Database: emotional paradigm",
+      "files": [],
+      "contributors": [
+        "Thirion, Bertrand",
+        "Pinel, Philippe",
+        "Poupon, Cyril",
+        "Grisel, Olivier",
+        "Varoquaux, Gaël"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Principal Component Regression Predicts Functional Responses across Individuals",
+          "cite": "Thirion, B., Varoquaux, G., Grisel, O., Poupon, C., & Pinel, P. (2014). Principal Component Regression Predicts Functional Responses across Individuals. Lecture Notes in Computer Science, 741–748. ",
+          "doi": "10.1007/978-3-319-10470-6_92"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "xlsx"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "DeFelipe, Javier"
+      ],
+      "description": "This dataset contains the density of tyrosine hydroxylase (TH)-immunoreactive cortical interneurons in various cytoarchitectonic areas of the human cerebral cortex. Cell density was analyzed on cell-body-stained histological sections of 2 human postmortem brains that were supplied by Dr R. Alcaraz, Forensic Pathology Service, Basque Institute of Legal Medicine, Bilbao, Spain.",
+      "licenseInfo": [],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Brodmann’s area 17"
+        },
+        {
+          "name": "Brodmann’s area 6"
+        },
+        {
+          "name": "Brodmann’s area 32"
+        },
+        {
+          "name": "Brodmann’s area 24"
+        },
+        {
+          "name": "Brodmann’s area 21"
+        },
+        {
+          "name": "Brodmann’s area 20"
+        },
+        {
+          "name": "Brodmann’s area 12"
+        },
+        {
+          "name": "Brodmann’s area 11"
+        },
+        {
+          "name": "Brodmann’s area 46"
+        },
+        {
+          "name": "Brodmann’s area 10"
+        },
+        {
+          "name": "Brodmann’s area 9"
+        }
+      ],
+      "name": "Distribution of neurons expressing tyrosine hydroxylase in the human cerebral cortex",
+      "files": [],
+      "contributors": [
+        "Benavides-Piccione, Ruth",
+        "DeFelipe, Javier"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Distribution of neurons expressing tyrosine hydroxylase in the human cerebral cortex",
+          "cite": "Benavides-Piccione, R., & DeFelipe, J. (2007). Distribution of neurons expressing tyrosine hydroxylase in the human cerebral cortex. Journal of Anatomy, 211(2), 212–222. ",
+          "doi": "10.1111/j.1469-7580.2007.00760.x"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area OP4 (POperc) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area OP4 (POperc). The probability map of Area OP4 (POperc) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-OP4.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area OP4 (POperc)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area OP4 (POperc)",
+      "files": [
+        {
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+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Mohlberg, Hartmut",
+        "Eickhoff, Simon B.",
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Schleicher, Axel"
+      ],
+      "kgReference": [
+        "10.25493/51S0-K7W"
+      ],
+      "publications": [
+        {
+          "name": "The Human Parietal Operculum. II. Stereotaxic Maps and Correlation with Functional Imaging Results",
+          "cite": "Eickhoff, S. B., Amunts, K., Mohlberg, H., & Zilles, K. (2005). The Human Parietal Operculum. II. Stereotaxic Maps and Correlation with Functional Imaging Results. Cerebral Cortex, 16(2), 268–279. ",
+          "doi": "10.1093/cercor/bhi106"
+        },
+        {
+          "name": "The Human Parietal Operculum. I. Cytoarchitectonic Mapping of Subdivisions",
+          "cite": "Eickhoff, S. B., Schleicher, A., Zilles, K., & Amunts, K. (2005). The Human Parietal Operculum. I. Cytoarchitectonic Mapping of Subdivisions. Cerebral Cortex, 16(2), 254–267. ",
+          "doi": "10.1093/cercor/bhi105"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Ch 4 (Basal Forebrain) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Ch 4 (Basal Forebrain). The probability map of Ch 4 (Basal Forebrain) is given in file jubrain-pmap-v22c_space-mnicolin27_BasalForebrain-Ch-4.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Ch 4 (Basal Forebrain)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Ch 4 (Basal Forebrain)",
+      "files": [
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_BasalForebrain-Ch-4.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_BasalForebrain-Ch-4.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Zaborszky, Laszlo",
+        "Zilles, Karl",
+        "Amunts, Katrin",
+        "Schleicher, Axel",
+        "Mohlberg, Hartmut",
+        "Hoemke, L."
+      ],
+      "kgReference": [
+        "10.25493/BWZ1-5MV"
+      ],
+      "publications": [
+        {
+          "name": "Stereotaxic probabilistic maps of the magnocellular cell groups in human basal forebrain",
+          "cite": "Zaborszky, L., Hoemke, L., Mohlberg, H., Schleicher, A., Amunts, K., & Zilles, K. (2008). Stereotaxic probabilistic maps of the magnocellular cell groups in human basal forebrain. NeuroImage, 42(3), 1127–1141. ",
+          "doi": "10.1016/j.neuroimage.2008.05.055"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Rostral Middle Frontal and Superior Frontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_RMF-SF_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_RMF-SF_0",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "rh_RMF-SF_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_RMF-SF_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [
+        {
+          "name": "Allen adult mouse brain reference atlas V3"
+        }
+      ],
+      "custodians": [
+        "Weber, Bruno"
+      ],
+      "description": "The goal of the study is to produce the first high resolution, 3D reconstruction of the entire macrostructure and vascular system of the mouse brain. To that end previously synchrotron radiation-based X-ray microscopy images were collected. Additionally recently two-photon microscopy images were collected. And we are looking for additional alternative imaging sources. Then this data is translated into 3D mesh and volumetric models (graph).  \nThis dataset contains the model of part of cortical vasculature of the mouse brain as a graph structure (discrete mathematics).  \nThe data is a derived dataset using computational methods from the dataset “3D imaging of the vascular system of the mouse brain” ([doi: 10.25493/3248-7V](https://doi.org/10.25493/3248-7V)).",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "3D reconstruction of the vascular system of the mouse brain.",
+      "files": [],
+      "contributors": [
+        "Erlebach, Eva",
+        "Efremov, Velizar",
+        "Weber, Bruno"
+      ],
+      "kgReference": [
+        "10.25493/47H2-1HR"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area hOc3d (Cuneus) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area hOc3d (Cuneus). The probability map of Area hOc3d (Cuneus) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-hOc3d.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area hOc3d (Cuneus)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area hOc3d (Cuneus)",
+      "files": [
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-hOc3d.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-hOc3d.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Kujovic, Milenko",
+        "Amunts, Katrin",
+        "Eickhoff, Simon B.",
+        "Rottschy, Claudia",
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Malikovic, Aleksandar",
+        "Zilles, Karl"
+      ],
+      "kgReference": [
+        "10.25493/SAMM-YKZ"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonic mapping of the human dorsal extrastriate cortex",
+          "cite": "Kujovic, M., Zilles, K., Malikovic, A., Schleicher, A., Mohlberg, H., Rottschy, C., … Amunts, K. (2012). Cytoarchitectonic mapping of the human dorsal extrastriate cortex. Brain Structure and Function, 218(1), 157–172. ",
+          "doi": "10.1007/s00429-012-0390-9"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [
+        {
+          "name": "Waxholm Space rat brain atlas v.2.0"
+        }
+      ],
+      "custodians": [
+        "Bos, Jeroen"
+      ],
+      "description": "The dataset includes spiking data from four areas (V2m, S1bf, perirhinal cortex, and hippocampal CA1) recording simultaneously in freely moving rats during a spatial navigation task with visual discrimination and memory components. Position data of the animals during the task obtained from video tracking is also provided. A more detailed overview of the experimental design and data collection process can be found in [1].\n**Embargo status:**   \n*This dataset is temporarily under embargo. The data will become available for download after the embargo period.*",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Multi-area recordings from visual and somatosensory cortices, perirhinal cortex and hippocampal CA1",
+      "files": [],
+      "contributors": [
+        "van Mourik-Donga, Laura A.",
+        "Pennartz, Cyriel",
+        "Witter, Menno P.",
+        "Jackson, Jadin C.",
+        "Vinck, Martin",
+        "Bos, Jeroen"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Perirhinal firing patterns are sustained across large spatial segments of the task environment",
+          "cite": "Bos, J. J., Vinck, M., van Mourik-Donga, L. A., Jackson, J. C., Witter, M. P., & Pennartz, C. M. A. (2017). Perirhinal firing patterns are sustained across large spatial segments of the task environment. Nature Communications, 8, 15602. ",
+          "doi": "10.1038/ncomms15602"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Riess, Olaf"
+      ],
+      "description": "Bright-field microscopy images of serial coronal brain sections showing Ca2+/calmodulin-dependent protein kinase II (Camk2a) promoter expression in a bigenic Camk2a-tetracycline-transactivator (tTA) mouse brain (case 317.8, adult female), using a driver-reporter construct in which the Camk2a-tTA promoter regulates the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, which is visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Methodological details are provided in Odeh et al., Neuroimage 54:2603-11, 2011. Our data show that the Camk2a-tTA promoter is spatially expressed in multiple brain regions, including the cerebral cortex, several basal ganglia regions, hippocampus, tectum, and cerebellum.",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Ca2+/calmodulin-dependent protein kinase II tetracycline-transactivator expression: coronal sections (case 317.8)",
+      "files": [],
+      "contributors": [
+        "Odeh, Francis",
+        "Riess, Olaf",
+        "Boy, Jana",
+        "Bjaalie, Jan G.",
+        "Schmidt, Thorsten",
+        "Leergaard, Trygve B."
+      ],
+      "kgReference": [
+        "10.25493/W97C-01R"
+      ],
+      "publications": [
+        {
+          "name": "Atlas of transgenic Tet-Off Ca2+/calmodulin-dependent protein kinase II and prion protein promoter activity in the mouse brain",
+          "cite": "Odeh, F., Leergaard, T. B., Boy, J., Schmidt, T., Riess, O., & Bjaalie, J. G. (2011). Atlas of transgenic Tet-Off Ca2+/calmodulin-dependent protein kinase II and prion protein promoter activity in the mouse brain. NeuroImage, 54(4), 2603–2611. ",
+          "doi": "10.1016/j.neuroimage.2010.11.032"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Inferior Temporal and Middle Temporal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_IT-MT_1"
+        }
+      ],
+      "name": "Probabilistic maps of rh_IT-MT_1",
+      "files": [
+        {
+          "byteSize": 156110,
+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 68240520,
+          "name": "rh_IT-MT_1.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_IT-MT_1.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
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+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
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+      "description": "This dataset contains the distinct architectonic Area hOc5 (LOC) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area hOc5 (LOC). The probability map of Area hOc5 (LOC) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-hOc5.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
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+        "Free"
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Eickhoff, Simon B.",
+        "Zilles, Karl",
+        "Armstrong, E.",
+        "Palomero-Gallagher, Nicola",
+        "Wilms, M.",
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Amunts, Katrin",
+        "Malikovic, Aleksandar"
+      ],
+      "kgReference": [
+        "10.25493/BPG7-360"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonic Analysis of the Human Extrastriate Cortex in the Region of V5/MT+: A Probabilistic, Stereotaxic Map of Area hOc5",
+          "cite": "Malikovic, A., Amunts, K., Schleicher, A., Mohlberg, H., Eickhoff, S. B., Wilms, M., … Zilles, K. (2006). Cytoarchitectonic Analysis of the Human Extrastriate Cortex in the Region of V5/MT+: A Probabilistic, Stereotaxic Map of Area hOc5. Cerebral Cortex, 17(3), 562–574. ",
+          "doi": "10.1093/cercor/bhj181"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
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+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Postcentral and Precentral gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_PoC-PrC_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_PoC-PrC_0",
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+          "contentType": "application/octet-stream"
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+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
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+      "formats": [
+        "Nifti Files, gifti files, csv files, json files"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Thirion, Bertrand"
+      ],
+      "description": "This dataset contains functional magnetic resonance images (fMRIs) of 12 subjects that examins functions involved in spatial cognition. The paradigm was structured in blocks and it comprised five block categories. Each block was formed by a set of trials containing an event, in which visual instructions related to one or two conditions of the same kind were displayed. These five categories of blocks were characterized as follows: (1) saccade, in which ocular movements were performed according to the displacement of a fixation across from the center toward peripheral locations in the image displayed; (2) imitation of object grasping with the right hand, in which the corresponding object was displayed on the screen; (3) mimic orientation of rhombus, displayed as image background on the screen, using the right hand; events of block categories 2 and 3 featured the same visual stimuli, in order to capture grasping-specific activity; (4) judgment on the left/right orientation of a hand displayed as visual stimulus; and (5) judgment on the palmar/dorsal direction of a hand displayed as visual stimulus. Events of block categories 4 and 5 featured the same visual stimuli. The task was constituted by forty blocks per run. The order of blocks presentation was pseudo-randomized for the session, but fixed for all participants. Each block was composed by either three or four trials. The duration of the trials ranged between 1.2 and 1.8 seconds. All blocks were inter-spaced by a fixation-cross period with a duration between four and six seconds.\n\n[https://openfmri.org/dataset/ds000244/](https://openfmri.org/dataset/ds000244/)\n\n[https://neurovault.org/collections/2138/](https://neurovault.org/collections/2138/)",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
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+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
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+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
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+      "publications": [
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+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
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+        }
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+      "name": "3D imaging of the vascular system of the mouse brain.",
+      "files": [],
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+        "Erlebach, Eva",
+        "Efremov, Velizar"
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+        "10.25493/3248-7V"
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+      "formats": [
+        "NIFTI"
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+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
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+      "custodians": [
+        "Amunts, Katrin"
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+      "description": "This dataset contains the distinct architectonic Area TE 1.0 (HESCHL) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area TE 1.0 (HESCHL). The probability map of Area TE 1.0 (HESCHL) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-TE-10.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
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+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area TE 1.0 (HESCHL)"
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+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Morosan, Patricia",
+        "Amunts, Katrin",
+        "Werner, C.",
+        "Freund, H.-J.",
+        "Schormann, Thorsten",
+        "Rademacher, Jörg"
+      ],
+      "kgReference": [
+        "10.25493/CP2T-FYT"
+      ],
+      "publications": [
+        {
+          "name": "Human Primary Auditory Cortex: Cytoarchitectonic Subdivisions and Mapping into a Spatial Reference System",
+          "cite": "Morosan, P., Rademacher, J., Schleicher, A., Amunts, K., Schormann, T., & Zilles, K. (2001). Human Primary Auditory Cortex: Cytoarchitectonic Subdivisions and Mapping into a Spatial Reference System. NeuroImage, 13(4), 684–701. ",
+          "doi": "10.1006/nimg.2000.0715"
+        },
+        {
+          "name": "Probabilistic Mapping and Volume Measurement of Human Primary Auditory Cortex",
+          "cite": "Rademacher, J., Morosan, P., Schormann, T., Schleicher, A., Werner, C., Freund, H.-J., & Zilles, K. (2001). Probabilistic Mapping and Volume Measurement of Human Primary Auditory Cortex. NeuroImage, 13(4), 669–683. ",
+          "doi": "10.1006/nimg.2000.0714"
+        }
+      ]
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+    {
+      "formats": [
+        "NIFTI"
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+        {
+          "name": "MNI Colin 27"
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+      "custodians": [
+        "Amunts, Katrin"
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+      "description": "This dataset contains the distinct architectonic CA2 (Hippocampus) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to CA2 (Hippocampus). The probability map of CA2 (Hippocampus) is given in file jubrain-pmap-v22c_space-mnicolin27_Hippocampus-CA2.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
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+      "parcellationRegion": [
+        {
+          "name": "CA2 (Hippocampus)"
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+      "contributors": [
+        "Shah, Nadim J.",
+        "Zilles, Karl",
+        "Schneider, F.",
+        "Habel, U.",
+        "Mohlberg, Hartmut",
+        "Pieperhoff, P.",
+        "Kindler, M.",
+        "Kedo, O.",
+        "Amunts, Katrin"
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+      "kgReference": [
+        "10.25493/1DJG-294"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps",
+          "cite": "Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N. J., … Zilles, K. (2005). Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and Embryology, 210(5-6), 343–352. ",
+          "doi": "10.1007/s00429-005-0025-5"
+        }
+      ]
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+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
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+      "description": "This dataset contains the distinct architectonic Area 4a (PreCG) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Area 4a (PreCG). The probability map of Area 4a (PreCG) is given in file jubrain-pmap-v22c_space-mnicolin27_ Area-4a.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
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+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 4a (PreCG)"
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+      "name": "Probabilistic cytoarchitectonic map of Area 4a (PreCG)",
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+      "contributors": [
+        "Klingberg, Torkel",
+        "Roland, Per E.",
+        "Zilles, Karl",
+        "Larsson, Jonas",
+        "Bürgel, Uli",
+        "Schormann, Thorsten",
+        "Kinomura, Shigeo",
+        "Schleicher, Axel",
+        "Ledberg, Anders",
+        "Geyer, Stefan"
+      ],
+      "kgReference": [
+        "10.25493/5GXC-Z2U"
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+      "publications": [
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+          "name": "Two different areas within the primary motor cortex of man",
+          "cite": "Geyer, S., Ledberg, A., Schleicher, A., Kinomura, S., Schormann, T., Bürgel, U., … Roland, P. E. (1996). Two different areas within the primary motor cortex of man. Nature, 382(6594), 805–807. ",
+          "doi": "10.1038/382805a0"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
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+      "custodians": [
+        "Poupon, Cyril"
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+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Lateral Orbitofrontal and Superior Temporal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
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+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
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+      "embargoStatus": [
+        "Free"
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+      "parcellationRegion": [
+        {
+          "name": "lh_LOF-ST_0"
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+      "name": "Probabilistic maps of lh_LOF-ST_0",
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+          "contentType": "application/octet-stream"
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+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
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+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
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+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area PGa (IPL) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area PGa (IPL). The probability map of Area PGa (IPL) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-PGa.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area PGa (IPL)"
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+      "name": "Probabilistic cytoarchitectonic map of Area PGa (IPL)",
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Mohlberg, Hartmut",
+        "Amunts, Katrin",
+        "Scheperjans, Filip",
+        "Geyer, Stefan",
+        "Schleicher, Axel",
+        "Caspers, S.",
+        "Eickhoff, Simon B.",
+        "Zilles, Karl"
+      ],
+      "kgReference": [
+        "10.25493/T96P-05Y"
+      ],
+      "publications": [
+        {
+          "name": "The human inferior parietal cortex: Cytoarchitectonic parcellation and interindividual variability",
+          "cite": "Caspers, S., Geyer, S., Schleicher, A., Mohlberg, H., Amunts, K., & Zilles, K. (2006). The human inferior parietal cortex: Cytoarchitectonic parcellation and interindividual variability. NeuroImage, 33(2), 430–448. ",
+          "doi": "10.1016/j.neuroimage.2006.06.054"
+        },
+        {
+          "name": "The human inferior parietal lobule in stereotaxic space",
+          "cite": "Caspers, S., Eickhoff, S. B., Geyer, S., Scheperjans, F., Mohlberg, H., Zilles, K., & Amunts, K. (2008). The human inferior parietal lobule in stereotaxic space. Brain Structure and Function, 212(6), 481–495. ",
+          "doi": "10.1007/s00429-008-0195-z"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Pars Opercularis and Insula gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_Op-Ins_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_Op-Ins_0",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the left hemisphere Caudal Middle Frontal and Rostral Middle Frontal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "lh_CMF-RMF_0"
+        }
+      ],
+      "name": "Probabilistic maps of lh_CMF-RMF_0",
+      "files": [
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+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Lateral Occipital and Superior Parietal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_LO-SP_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_LO-SP_0",
+      "files": [
+        {
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+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_LO-SP_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Precentral and Superior Parietal gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_PrC-SP_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_PrC-SP_0",
+      "files": [
+        {
+          "byteSize": 68240520,
+          "name": "rh_PrC-SP_0.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_PrC-SP_0.nii",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Cherubini, Enrico"
+      ],
+      "description": "A general procedure to fit individual synaptic events recorded from voltage clamp experiments was tested with various sets of experimental data on GABAergic synapses; gephyrin and gephyrin-dependent pathways were chosen as a suitable example of a kinetic model of synaptic transmission. The data used here are obtained from coronal hippocampal slices (300 μm thick) from 3 to 4 months old Tg2576 (carrying the Amyloid Precursor Protein KM670/671NL Swedish mutation) female mice. The dataset contains 1000 individual events recorded from 10 different neurons (expE1-E10). The first column of each txt file contains the time in ms and the other columns contain spontaneous inhibitory synaptic currents (sIPSCs) in pA.\nComputational modeling of brain circuits requires the definition of many parameters that are difficult to determine from experimental findings. One way to help interpret these data is to fit them using a particular kinetic model. In [1] we proposed a general procedure to fit individual synaptic events recorded from voltage clamp experiments. Starting from any given model description (mod file) in the NEURON simulation environment, the procedure exploits user-defined constraints, dependencies, and rules for the parameters of the model to fit the time course of individual spontaneous synaptic events that are recorded experimentally. A Python version is available for public use, as a Jupyter Notebook in the Collaboratory Portal of the Human Brain Project. To illustrate the potential application of the procedure, we tested its use with various sets of experimental data on GABAergic synapses; gephyrin and gephyrin-dependent pathways were chosen as a suitable example of a kinetic model of synaptic transmission. For individual spontaneous inhibitory events in hippocampal pyramidal CA1 neurons, we found that gephyrin-dependent subcellular pathways may shape synaptic events at different levels, and can be correlated with cell- or event-specific activity history and/or pathological conditions.\nFitting experimental data against a number of different models is a common way to do this (reviewed in [2]), and can help in the subsequent interpretation of the data. In general, experimental traces are fitted using specific approaches for specific purposes (e.g., [3], [4]). However, to the best of our knowledge, there is no easy, user-friendly, general procedure available for this purpose, especially in computational neuroscience. Our aim was thus to identify the appropriate conceptual structure of a procedure to obtain good, reliable fits of raw experimental traces of spontaneous synaptic events. This is an important step because spontaneous synaptic events have been so far exclusively analyzed using traces obtained by averaging many events. However, as can be easily imagined, each synapse in any given neuron has its own, independent, history of activation. The most likely physiological consequence is that the variables relative to the subcellular processes underlying synaptic transmission are different for each synapse. If a researcher is interested in testing a specific kinetic scheme implemented for specific biochemical pathways, the use of individual events is the most appropriate choice, since this approach would give information on the different combinations of model parameters that are consistent with the observed events. Averaging traces will lose a lot of relevant information.\nWe therefore present here the implementation of a procedure leading to the development of a unifying optimization method for individual synaptic events. Experimental data, kinetic models of synaptic transmission, and fitting parameters and their dependencies can be user defined/provided or gathered from databases. They can be used to generate optimized groups of parameters able to represent a population of synapses, either for simulation purposes or to study the functional consequences of a particular protein or subcellular synaptic transmission pathway.\n[1] Lupascu CA, Morabito A, Merenda E, et al. A General Procedure to Study Subcellular Models of Transsynaptic Signaling at Inhibitory Synapses. Frontiers in Neuroinformatics. 2016;10:23. doi:10.3389/fninf.2016.00023.  \n[2] Van Geit W., De Schutter E., Achard P. (2008). Automated neuron model optimization techniques: a review. Biol. Cybern. 99, 241–251. 10.1007/s00422-008-0257-6  \n[3] Bekkers J. M. (2003). Convolution of mini distributions for fitting evoked synaptic amplitude histograms. J. Neurosci. Methods. 130, 105–114. 10.1016/j.jneumeth.2003.09.018  \n[4] Meisl G., Kirkegaard J. B., Arosio P., Michaels T. C., Vendruscolo M., Dobson C. M., et al. . (2016). Molecular mechanisms of protein aggregation from global fitting of kinetic models. Nat. Protoc. 11, 252–272. 10.1038/nprot.2016.010",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Spontaneous inhibitory post-synaptic currents recorded from CA1 pyramidal neurons of adult wild type Tg2576 mice",
+      "files": [],
+      "contributors": [
+        "Cherubini, Enrico",
+        "Marinelli, Silvia",
+        "Marchetti, Cristina"
+      ],
+      "kgReference": [
+        "10.25493/CTAV-Q45"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area hOc4v (LingG) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area hOc4v (LingG). The probability map of Area hOc4v (LingG) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-hOc4v.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area hOc4v (LingG)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area hOc4v (LingG)",
+      "files": [
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+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
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+        {
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+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-hOc4v.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-hOc4v.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Rottschy, Claudia",
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Kujovic, Milenko",
+        "Mohlberg, Hartmut",
+        "Schleicher, Axel",
+        "Eickhoff, Simon B."
+      ],
+      "kgReference": [
+        "10.25493/E0YJ-ADE"
+      ],
+      "publications": [
+        {
+          "name": "Ventral visual cortex in humans: Cytoarchitectonic mapping of two extrastriate areas",
+          "cite": "Rottschy, C., Eickhoff, S. B., Schleicher, A., Mohlberg, H., Kujovic, M., Zilles, K., & Amunts, K. (2007). Ventral visual cortex in humans: Cytoarchitectonic mapping of two extrastriate areas. Human Brain Mapping, 28(10), 1045–1059. ",
+          "doi": "10.1002/hbm.20348"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [
+        {
+          "name": "Allen adult mouse brain reference atlas V3"
+        }
+      ],
+      "custodians": [
+        "D'Angelo, Egidio"
+      ],
+      "description": "Study and characterization of the intrinsic properties of Golgi cells.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Recordings of spontaneous firing of cerebellar interneurons (Golgi cells)",
+      "files": [],
+      "contributors": [
+        "Tognolina, Marialuisa",
+        "D'Angelo, Egidio",
+        "Locatelli, Francesca"
+      ],
+      "kgReference": [
+        "10.25493/JQH3-0A4"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "Nifti Files, gifti files, csv files, json files"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Thirion, Bertrand"
+      ],
+      "description": "This dataset contains functional magnetic resonance images (fMRIs) of 12 subjects performing HCP Working Memory (HCP WM) task that was adapted from the classical n-back task to serve as functional localizer for evaluation of structures involved in working memory (WM). The paradigm included two categories of blocks, namely the “0-back” and “2- back” WM-task blocks. They were both equally presented within a run. A cue was always displayed at the beginning of each block, indicating its block type. Blocks were formed by sets of events, during which pictures of faces, places, tools or body parts were shown on the screen. One block was always dedicated to one specific category of pictures and the four categories were always presented during every run. The task was constituted by sixteen blocks per run, eight per n-back category. Besides, there were four pairs of blocks per visual category. The order of the blocks, regardless of their category and corresponding class of pictures, was pseudo-randomized for every run, but fixed for all participants. A fixationcross period of fifteen seconds was introduced between some blocks. All blocks contained ten trials; they were initiated by a cue during 2.5 seconds. Trials included in turn the presentation of a picture for two seconds and a very short fixation-cross period for half of a second; the total duration of one trial was thus 2.5 seconds.\n\n[https://openfmri.org/dataset/ds000244/](https://openfmri.org/dataset/ds000244/)\n\n[https://neurovault.org/collections/2138/](https://neurovault.org/collections/2138/)",
+      "licenseInfo": [
+        "Creative Commons CC0 - No Rights Reserved"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Individual Brain Charting: HCP Working Memory task",
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+        "Thirion, Bertrand",
+        "Hertz-Pannier, Lucie",
+        "Dehaene, Stanislas",
+        "Pallier, Christophe",
+        "Varoquaux, Gaël",
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+        "Pinel, Philippe",
+        "Martins, Bernadette",
+        "Doublé, Christine",
+        "Médiouni-Cloarec, Gaëlle",
+        "Joly-Testault, Véronique",
+        "Laurier, Laurence",
+        "Roger, Séverine",
+        "Becuwe-Desmidt, Séverine",
+        "Ginisty, Chantal",
+        "Denghien, Isabelle",
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+        "Pimpinella, Domenico",
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+        "Guevara, Pamela",
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+        "Caspers, S.",
+        "Friederici, Angela D.",
+        "Amunts, Katrin",
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+          "doi": "10.1016/j.cortex.2014.07.007"
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+          "cite": "Caspers, S., Schleicher, A., Bacha-Trams, M., Palomero-Gallagher, N., Amunts, K., & Zilles, K. (2012). Organization of the Human Inferior Parietal Lobule Based on Receptor Architectonics. Cerebral Cortex, 23(3), 615–628. ",
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+      "licenseInfo": [
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+      "licenseInfo": [
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+        "Guevara, Pamela",
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+        "Duclap, Delphine",
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+        "Jankowsky, Joanna L."
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+      "description": "Bright-field microscopy images of serial coronal brain sections showing Pituitary homeobox 3 (Pitx3) promoter expression in a bigenic Pitx3-tetracycline-transactivator (tTA) mouse brain (case 6517, adult female), using a driver-reporter construct in which the Pitx3-tTA promoter regulates the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, which is visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Our data show that the Pitx3-tTA promoter is spatially restricted to the substantia nigra, ventral tegmental area, and a few other regions.",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Pituitary homeobox 3 tetracycline-transactivator expression: coronal sections (case 6517)",
+      "files": [],
+      "contributors": [
+        "Yetman, Michael J.",
+        "Lillehaug, Sveinung",
+        "Bjaalie, Jan G.",
+        "Checinska, Martyna M.",
+        "Puchades, Maja A.",
+        "Jankowsky, Joanna L.",
+        "Leergaard, Trygve B."
+      ],
+      "kgReference": [
+        "10.25493/DTB3-0KP"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [
+        {
+          "name": "Allen adult mouse brain reference atlas V2"
+        }
+      ],
+      "custodians": [
+        "Jankowsky, Joanna L."
+      ],
+      "description": "Bright-field microscopy images of serial coronal brain sections showing neuropsin (Nop) promoter expression in a bigenic Nop-tetracycline-transactivator (tTA) mouse brain (case 1952 adult male), using a driver-reporter construct in which the Nop-tTA promoter regulates the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, which is visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Methodological details are provided in Yetman et al., Brain Struct Funct 221:2231-49, 2016. Our data show that the Nop-tTA promoter mainly is expressed in the entorhinal cortex, but also in several other cortical regions.",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Neuropsin tetracycline-transactivator expression: coronal sections (case 1952)",
+      "files": [],
+      "contributors": [
+        "Leergaard, Trygve B.",
+        "Lillehaug, Sveinung",
+        "Bjaalie, Jan G.",
+        "Jankowsky, Joanna L.",
+        "Yetman, Michael J."
+      ],
+      "kgReference": [
+        "10.25493/5H13-1Q0"
+      ],
+      "publications": [
+        {
+          "name": "Transgene expression in the Nop-tTA driver line is not inherently restricted to the entorhinal cortex",
+          "cite": "Yetman, M. J., Lillehaug, S., Bjaalie, J. G., Leergaard, T. B., & Jankowsky, J. L. (2015). Transgene expression in the Nop-tTA driver line is not inherently restricted to the entorhinal cortex. Brain Structure and Function, 221(4), 2231–2249. ",
+          "doi": "10.1007/s00429-015-1040-9"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area OP3 (POperc) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area OP3 (POperc). The probability map of Area OP3 (POperc) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-OP3.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area OP3 (POperc)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area OP3 (POperc)",
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Eickhoff, Simon B.",
+        "Mohlberg, Hartmut"
+      ],
+      "kgReference": [
+        "10.25493/6PRT-2PS"
+      ],
+      "publications": [
+        {
+          "name": "The Human Parietal Operculum. II. Stereotaxic Maps and Correlation with Functional Imaging Results",
+          "cite": "Eickhoff, S. B., Amunts, K., Mohlberg, H., & Zilles, K. (2005). The Human Parietal Operculum. II. Stereotaxic Maps and Correlation with Functional Imaging Results. Cerebral Cortex, 16(2), 268–279. ",
+          "doi": "10.1093/cercor/bhi106"
+        },
+        {
+          "name": "The Human Parietal Operculum. I. Cytoarchitectonic Mapping of Subdivisions",
+          "cite": "Eickhoff, S. B., Schleicher, A., Zilles, K., & Amunts, K. (2005). The Human Parietal Operculum. I. Cytoarchitectonic Mapping of Subdivisions. Cerebral Cortex, 16(2), 254–267. ",
+          "doi": "10.1093/cercor/bhi105"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [],
+      "custodians": [
+        "Gulyás, Attila"
+      ],
+      "description": "Understanding cortical circuits requires the characterization of their constituent neurons.\nUsing whole-cell recordings in acute hippocampal slices, followed by confocal imaging and 3D reconstruction,\na database of the morphological and physiological properties of hippocampal neurons has been constructed.\nThe database currently contains approximately 200 morphological reconstructions and 500 recordings\nfrom partially overlapping cell populations.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "parcellationRegion": [],
+      "name": "Morphological and physiological database of excitatory and inhibitory cell types of the mouse hippocampus",
+      "files": [],
+      "contributors": [
+        "Kohus, Zsolt",
+        "Schlingloff, Dániel",
+        "Berki, Péter",
+        "Gulyás, Attila",
+        "Kriczky, Nándor"
+      ],
+      "kgReference": [],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Poupon, Cyril"
+      ],
+      "description": "This data contains the probability map of a short fiber bundle connecting the right hemisphere Caudal Anterior Cingulate and Precuneus gyri, in the MNI152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fiber shape (fiber clustering), from the tractography datasets of 77 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fiber belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibers going though.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "rh_CAC-PrCu_0"
+        }
+      ],
+      "name": "Probabilistic maps of rh_CAC-PrCu_0",
+      "files": [
+        {
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+          "name": "short-bundles_maxprob.nii.gz",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/short-bundles_maxprob.nii.gz",
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+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000339/right hemisphere/Probability_Maps/rh_CAC-PrCu_0.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Guevara, Miguel",
+        "Guevara, Pamela",
+        "Mangin, Jean-François",
+        "Poupon, Cyril",
+        "Duclap, Delphine",
+        "Houenou, Josselin",
+        "Román, Claudio"
+      ],
+      "kgReference": [],
+      "publications": [
+        {
+          "name": "Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography",
+          "cite": "Guevara, M., Román, C., Houenou, J., Duclap, D., Poupon, C., Mangin, J. F., & Guevara, P. (2017). Reproducibility of superficial white matter tracts using diffusion-weighted imaging tractography. NeuroImage, 147, 703–725. ",
+          "doi": "10.1016/j.neuroimage.2016.11.066"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic SF (Amygdala) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to SF (Amygdala). The probability map of SF (Amygdala) is given in file jubrain-pmap-v22c_space-mnicolin27_Amygdala-SF.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "SF (Amygdala)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of SF (Amygdala)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Amygdala-SF.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Amygdala-SF.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
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+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Habel, U.",
+        "Zilles, Karl",
+        "Schneider, F.",
+        "Shah, Nadim J.",
+        "Mohlberg, Hartmut",
+        "Pieperhoff, P.",
+        "Kindler, M.",
+        "Kedo, O.",
+        "Amunts, Katrin"
+      ],
+      "kgReference": [
+        "10.25493/BRNZ-SXW"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps",
+          "cite": "Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N. J., … Zilles, K. (2005). Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and Embryology, 210(5-6), 343–352. ",
+          "doi": "10.1007/s00429-005-0025-5"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "3D TIFF"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Pavone, Francesco S."
+      ],
+      "description": "This dataset contains the image of spatial distribution of GABA receptor in human cortex using serial two photons microscopy. The individual 3D tiles acquired with the two photon fluorescence microscope were fused together to produce the final image.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Visual cortex area 17"
+        }
+      ],
+      "name": "Maps of GABA receptors in human cortex",
+      "files": [
+        {
+          "byteSize": 7677059308,
+          "name": "gaba.tiff",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000772/gaba.tiff",
+          "contentType": "image/tiff"
+        }
+      ],
+      "contributors": [
+        "Costantini, Irene",
+        "Pavone, Francesco S."
+      ],
+      "kgReference": [
+        "10.25493/EXHA-95S"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area 3a (PostCG) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area 3a (PostCG). The probability map of Area 3a (PostCG) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-3a.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 3a (PostCG)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area 3a (PostCG)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-3a.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-3a.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Mohlberg, Hartmut",
+        "Geyer, Stefan",
+        "Schleicher, Axel",
+        "Schormann, Thorsten",
+        "Zilles, Karl"
+      ],
+      "kgReference": [
+        "10.25493/R19N-B8E"
+      ],
+      "publications": [
+        {
+          "name": "Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex",
+          "cite": "Geyer, S., Schleicher, A., & Zilles, K. (1999). Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex. NeuroImage, 10(1), 63–83. ",
+          "doi": "10.1006/nimg.1999.0440"
+        },
+        {
+          "name": "Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex",
+          "cite": "Geyer, S., Schormann, T., Mohlberg, H., & Zilles, K. (2000). Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex. NeuroImage, 11(6), 684–696. ",
+          "doi": "10.1006/nimg.2000.0548"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area Ig2 (Insula) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Area Ig2 (Insula). The probability map of Area Ig2 (Insula) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-Ig2.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area Ig2 (Insula)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area Ig2 (Insula)",
+      "files": [
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-Ig2.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-Ig2.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Kurth, F.",
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Hoemke, L.",
+        "Schleicher, Axel",
+        "Eickhoff, Simon B."
+      ],
+      "kgReference": [
+        "10.25493/N7C7-BHW"
+      ],
+      "publications": [
+        {
+          "name": "Cytoarchitecture and Probabilistic Maps of the Human Posterior Insular Cortex",
+          "cite": "Kurth, F., Eickhoff, S. B., Schleicher, A., Hoemke, L., Zilles, K., & Amunts, K. (2009). Cytoarchitecture and Probabilistic Maps of the Human Posterior Insular Cortex. Cerebral Cortex, 20(6), 1448–1461. ",
+          "doi": "10.1093/cercor/bhp208"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area OP1 (POperc) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area OP1 (POperc). The probability map of Area OP1 (POperc) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-OP1.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area OP1 (POperc)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area OP1 (POperc)",
+      "files": [
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
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+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-OP1.nii",
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+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Amunts, Katrin",
+        "Zilles, Karl",
+        "Mohlberg, Hartmut",
+        "Eickhoff, Simon B.",
+        "Schleicher, Axel"
+      ],
+      "kgReference": [
+        "10.25493/HVH9-KBR"
+      ],
+      "publications": [
+        {
+          "name": "The Human Parietal Operculum. I. Cytoarchitectonic Mapping of Subdivisions",
+          "cite": "Eickhoff, S. B., Schleicher, A., Zilles, K., & Amunts, K. (2005). The Human Parietal Operculum. I. Cytoarchitectonic Mapping of Subdivisions. Cerebral Cortex, 16(2), 254–267. ",
+          "doi": "10.1093/cercor/bhi105"
+        },
+        {
+          "name": "The Human Parietal Operculum. II. Stereotaxic Maps and Correlation with Functional Imaging Results",
+          "cite": "Eickhoff, S. B., Amunts, K., Mohlberg, H., & Zilles, K. (2005). The Human Parietal Operculum. II. Stereotaxic Maps and Correlation with Functional Imaging Results. Cerebral Cortex, 16(2), 268–279. ",
+          "doi": "10.1093/cercor/bhi106"
+        }
+      ]
+    },
+    {
+      "formats": [],
+      "referenceSpaces": [
+        {
+          "name": "Allen adult mouse brain reference atlas V2"
+        }
+      ],
+      "custodians": [
+        "Leergaard, Trygve B."
+      ],
+      "description": "Tabular overview (csv format) of brain-wide reporter expression mapped in five commonly used tetracycline-transactivator (tTA) driver lines: neuropsin (Nop); L7/Purkinje cell protein 2 (Pcp2); Pituitary homeobox 3 (Pitx3); cellular prion protein (Prnp), and Ca2+/calmodulin-dependent protein kinase IIa (Camk2a).  This analysis is derived from microscopic brain images taken from 12 driver-reporter constructs (DOIs for source data sets are specified in data descriptor file listed below; hbp-00170\\_Comparative\\_DataDescriptor\\_v1p1.txt) in which the different promoters regulate the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Labelling was observed in microscopic images that were spatially registered to the Allen Mouse Common Coordinate Framework (v2; mouse.brain-map.org). The density of labeling was assessed by two independent researchers using a semi-quantitative grading system from 0 – 4, introduced in Yetman et al., Brain Struct Funct 221:2231-49, 2016. Here grade 0 represents absence of labeled cells (less than 1 per 0.01 mm2), grade 1 - low density (few cells, possible to count), grade 2 - medium density (several cells that can be individually discerned, but not readily counted), grade 3 - high density (many labeled cells with large degree of overlap), and grade 4 - very high density (where individual cells cannot be discerned). For each promoter-tTA line one representative case was semi-quantitatively scored and results verified in the other cases. Scores did not vary more than 1 grade between cases or researchers in any regions. The highest numbers were reported. If the density of labeling was found to vary substantially within a region, the highest observed score was recorded.",
+      "licenseInfo": [
+        "Creative Commons Attribution 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [],
+      "name": "Comparative overview of brain-wide tetracycline-transactivator expression",
+      "files": [],
+      "contributors": [
+        "Puchades, Maja A.",
+        "Bjaalie, Jan G.",
+        "Lillehaug, Sveinung",
+        "Leergaard, Trygve B.",
+        "Jankowsky, Joanna L.",
+        "Kleven, Heidi",
+        "Checinska, Martyna M.",
+        "Yetman, Michael J."
+      ],
+      "kgReference": [
+        "10.25493/ARKS-R7H"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "3D-TIFF"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Pavone, Francesco S."
+      ],
+      "description": "This dataset contains images of astrocytes in the human cortex obtained using serial two-photon microscopy. The individual 3D tiles acquired with the two photon fluorescence microscope were fused together to produce the final image.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Visual cortex area 17"
+        }
+      ],
+      "name": "Map of astrocytes in human brain cortex",
+      "files": [
+        {
+          "byteSize": 2399916287,
+          "name": "mosaic2.tiff",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/hbp-data-000326/mosaic2.tiff",
+          "contentType": "image/tiff"
+        }
+      ],
+      "contributors": [
+        "Costantini, Irene",
+        "Pavone, Francesco S."
+      ],
+      "kgReference": [
+        "10.25493/6RNR-BDX"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "xlsx, tif, txt"
+      ],
+      "referenceSpaces": [],
+      "custodians": [
+        "Zilles, Karl",
+        "Palomero-Gallagher, Nicola"
+      ],
+      "description": "This dataset contains the densities (in fmol/mg protein) of 16 receptors for classical neurotransmitters in the Globus Pallidus using quantitative in vitro autoradiography. The receptor density measurements can be provided in three ways: (fp) as density fingerprints (average across samples; mean density and standard deviation for each of the 16 receptors), (pr) as laminar density profiles (exemplary data from one sample; average course of the density from the pial surface to the border between layer VI and the white matter for each receptor), and (ar) as color-coded autoradiographs (exemplary data from one sample; laminar density distribution patterns for each receptor labeling). \nThis dataset contains the following receptor density measurements based on the labeling of these receptor binding sites: \n\nAMPA (glutamate; labelled with [³H]AMPA): fp\n\nkainate (glutamate; [³H]kainate): fp\n\nNMDA (glutamate; [³H]MK-801): fp\n\nGABA<sub>A</sub> (GABA; [³H]muscimol): fp\n\nGABA<sub>B</sub> (GABA; [³H] CGP54626): fp\n\nGABA<sub>A</sub> associated benzodiazepine binding sites (BZ; [³H]flumazenil): fp\n\nmuscarinic M₁ (acetylcholine; [³H]pirenzepine): fp\n\nmuscarinic M₂ (acetylcholine; [³H]oxotremorine-M): fp\n\nmuscarinic M₃ (acetylcholine; [³H]4-DAMP): fp\n\nnicotinic α₄β₂ (acetylcholine; [³H]epibatidine): fp\n\nα₁ (noradrenalin; [³H]prazosin): fp\n\nα₂ (noradrenalin; [³H]UK-14,304): fp\n\n5-HT₁<sub>A</sub> (serotonin; [³H]8-OH-DPAT): fp\n\n5-HT₂ (serotonin; [³H]ketanserin): fp\n\nD₁ (dopamine; [³H]SCH23390): fp\n\nWhich sample was used for which receptor density measurement is stated in metadata files accompanying the main data repository. For methodological details, see Zilles et al. (2002), and in Palomero-Gallagher and Zilles (2018).\n\nZilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press.\n\nPalomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Globus Pallidus"
+        }
+      ],
+      "name": "Density measurements of different receptors for Globus Pallidus",
+      "files": [
+        {
+          "byteSize": 15948,
+          "name": "GP_fp_20180405.xlsx",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/data_derived/Nucleus_GP/GP_fp_20180405.xlsx",
+          "contentType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        },
+        {
+          "byteSize": 44096,
+          "name": "metadata.zip",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/Receptors/metadata.zip",
+          "contentType": "application/zip"
+        }
+      ],
+      "contributors": [
+        "Palomero-Gallagher, Nicola"
+      ],
+      "kgReference": [
+        "10.25493/TPRG-5VH"
+      ],
+      "publications": []
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area 4p (PreCG) in the MNI Colin 27 reference. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference where each voxel is assigned with the probability to belong to Area 4p (PreCG). The probability map of Area 4p (PreCG) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-4p.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 4p (PreCG)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area 4p (PreCG)",
+      "files": [
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-4p.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-4p.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Klingberg, Torkel",
+        "Roland, Per E.",
+        "Zilles, Karl",
+        "Larsson, Jonas",
+        "Bürgel, Uli",
+        "Schormann, Thorsten",
+        "Kinomura, Shigeo",
+        "Schleicher, Axel",
+        "Ledberg, Anders",
+        "Geyer, Stefan"
+      ],
+      "kgReference": [
+        "10.25493/ECYA-0D1"
+      ],
+      "publications": [
+        {
+          "name": "Two different areas within the primary motor cortex of man",
+          "cite": "Geyer, S., Ledberg, A., Schleicher, A., Kinomura, S., Schormann, T., Bürgel, U., … Roland, P. E. (1996). Two different areas within the primary motor cortex of man. Nature, 382(6594), 805–807. ",
+          "doi": "10.1038/382805a0"
+        }
+      ]
+    },
+    {
+      "formats": [
+        "NIFTI"
+      ],
+      "referenceSpaces": [
+        {
+          "name": "MNI Colin 27"
+        }
+      ],
+      "custodians": [
+        "Amunts, Katrin"
+      ],
+      "description": "This dataset contains the distinct architectonic Area 7A (SPL) in the MNI Colin 27 reference brain. As part of the JuBrain atlas, the area was identified using classical histological criteria and quantitative cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 reference brain where each voxel is assigned with the probability to belong to Area 7A (SPL). The probability map of Area 7A (SPL) is given in file jubrain-pmap-v22c_space-mnicolin27_Area-7A.nii. The JuBrain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.",
+      "licenseInfo": [
+        "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International"
+      ],
+      "embargoStatus": [
+        "Free"
+      ],
+      "license": [],
+      "parcellationRegion": [
+        {
+          "name": "Area 7A (SPL)"
+        }
+      ],
+      "name": "Probabilistic cytoarchitectonic map of Area 7A (SPL)",
+      "files": [
+        {
+          "byteSize": 17487360,
+          "name": "jubrain-pmap-v22c_space-mnicolin27_Area-7A.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-pmap-v22c_space-mnicolin27_Area-7A.nii",
+          "contentType": "application/octet-stream"
+        },
+        {
+          "byteSize": 4372104,
+          "name": "jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "absolutePath": "https://object.cscs.ch/v1/AUTH_227176556f3c4bb38df9feea4b91200c/JuBrain/data-derived/jubrain-pmaps-v22c/jubrain-max-pmap-v22c_space-mnicolin27.nii",
+          "contentType": "application/octet-stream"
+        }
+      ],
+      "contributors": [
+        "Zilles, Karl",
+        "Schleicher, Axel",
+        "Hermann, K.",
+        "Scheperjans, Filip",
+        "Eickhoff, Simon B.",
+        "Mohlberg, Hartmut",
+        "Amunts, Katrin",
+        "Hoemke, L."
+      ],
+      "kgReference": [
+        "10.25493/MQ4V-YRR"
+      ],
+      "publications": [
+        {
+          "name": "Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Hermann, K., Eickhoff, S. B., Amunts, K., Schleicher, A., & Zilles, K. (2007). Observer-Independent Cytoarchitectonic Mapping of the Human Superior Parietal Cortex. Cerebral Cortex, 18(4), 846–867. ",
+          "doi": "10.1093/cercor/bhm116"
+        },
+        {
+          "name": "Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex",
+          "cite": "Scheperjans, F., Eickhoff, S. B., Hoemke, L., Mohlberg, H., Hermann, K., Amunts, K., & Zilles, K. (2008). Probabilistic Maps, Morphometry, and Variability of Cytoarchitectonic Areas in the Human Superior Parietal Cortex. Cerebral Cortex, 18(9), 2141–2157. ",
+          "doi": "10.1093/cercor/bhm241"
+        }
+      ]
+    }
+  ],
+  "total": 347,
+  "size": 450,
+  "start": 0
+}
\ No newline at end of file
diff --git a/src/res/ext/camillaWaxholmPointsAggregatedData.json b/src/res/ext/camillaWaxholmPointsAggregatedData.json
index ad504a85726ec3f6392162c3d6ec9d1fbaa724c3..46f83655c43787c882055e600b699a5d767baa5c 100644
--- a/src/res/ext/camillaWaxholmPointsAggregatedData.json
+++ b/src/res/ext/camillaWaxholmPointsAggregatedData.json
@@ -1 +1 @@
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Ground","templateSpace":"Waxholm Rat V2.0","geometry":{"type":"point","space":"real","position":[-0.05859350000000063,-9.550780499999998,7.089843999999999],"properties":{"description":"Description of Ground","publications":[]}}},{"name":"hbp-00941_ERP.json - hbp-00941_ERP_j10_hippo-histo","templateSpace":"Waxholm Rat V2.0","geometry":{"type":"point","space":"real","position":[2.0976564999999994,-2.5273429999999983,3.5234377499999994],"properties":{"description":"Description of hbp-00941_ERP_j10_hippo-histo","publications":[]}}},{"name":"hbp-00941_ERP.json - hbp-00941_ERP_j10_histo-M2_nr1","templateSpace":"Waxholm Rat V2.0","geometry":{"type":"point","space":"real","position":[-1.0781247500000006,4.984375750000002,4.996093999999999],"properties":{"description":"Description of hbp-00941_ERP_j10_histo-M2_nr1","publications":[]}}},{"name":"hbp-00941_ERP.json - hbp-00941_ERP_j10_histo-M2_nr2","templateSpace":"Waxholm Rat V2.0","geometry":{"type":"point","space":"real","position":[-1.4804685000000006,4.957032000000002,5.007812749999999],"properties":{"description":"Description of hbp-00941_ERP_j10_histo-M2_nr2","publications":[]}}},{"name":"hbp-00941_ERP.json - 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diff --git a/src/res/ext/pmapsAggregatedData.json b/src/res/ext/pmapsAggregatedData.json
index 668f4415b4bb522cd33014c9d82a62d741280be5..23f486e60c3daaf991bdb549f82a2466fc257b0e 100644
--- a/src/res/ext/pmapsAggregatedData.json
+++ b/src/res/ext/pmapsAggregatedData.json
@@ -1 +1,2739 @@
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diff --git a/src/res/ext/waxholmRatV2_0.json b/src/res/ext/waxholmRatV2_0.json
index e5fc1c61c35773dc4ec6aa46a0277114fb9d04d4..1421ce2d0aab60d5f00c86ac16c1a21a5fb458a6 100644
--- a/src/res/ext/waxholmRatV2_0.json
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Spatial reference is provided by the Waxholm Space coordinate system."}}
\ No newline at end of file
+{"name":"Waxholm Space rat brain atlas v.2.0","type":"template","species":"Rat","useTheme":"dark","nehubaConfigURL":"res/json/waxholmRatV2_0NehubaConfig.json","parcellations":[{"ngId":"whole","type":"parcellation","name":"Whole Brain (v2.0)","ngData":null,"regions":[{"name":"White matter","description":null,"parent_name":null,"synonyms":[""],"acronyms":[""],"labelIndex":null,"rgb":null,"children":[{"name":"corpus callosum and associated subcortical white matter","description":null,"parent_name":"White matter","synonyms":[""],"acronyms":[""],"labelIndex":67,"rgb":[255,110,0],"children":null},{"name":"Anterior commissure","description":null,"parent_name":"White matter","synonyms":[""],"acronyms":[""],"labelIndex":null,"rgb":null,"children":[{"name":"anterior commissure, anterior part","description":null,"parent_name":"Anterior commissure","synonyms":[""],"acronyms":[""],"labelIndex":36,"rgb":[124,252,0],"children":null},{"name":"anterior commissure, posterior 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\ No newline at end of file
diff --git a/src/services/stateStore.service.ts b/src/services/stateStore.service.ts
index 5905dfe2699df9a88442d26b687727a8b57fbe05..c39292834d3f6a2dbed3863efa7ffa0a34173069 100644
--- a/src/services/stateStore.service.ts
+++ b/src/services/stateStore.service.ts
@@ -370,29 +370,51 @@ export interface DedicatedViewAction extends Action{
   dedicatedView : string | null
 }
 
-export interface DataEntry{
-  type : string
-  name : string
-  kgID? : string
-  regionName : {
-    regionName : string,
-    relationship : string
-  }[]
+export interface KgInfo{
+  kgId?: string
+  descrption? : string
+  /**
+   * perhaps have contributors as a separate interface?
+   */
+  contributors? : string[]
+  publications?: Publication[]
+  preparations?: string[]
+  methods?: string[]
+  license?: string
+  files? : File[]
 
-  properties : Property
+  kgUri? : string
+}
 
+export interface DataEntry{
+  name: string
+  description: string
+  license: string[]
+  licenseInfo: string[]
+  parcellationRegion: ParcellationRegion[]
+  formats: string[]
+  custodians: string[]
+  contributors: string[]
+  referenceSpaces: ReferenceSpace[]
   files : File[]
+  publications: Publication[]
+  embargoStatus: string[]
+
+  /**
+   * TODO typo, should be kgReferences
+   */
+  kgReference: string[]
 }
 
 export interface File{
-  filename : string
-  name : string
-  mimetype : string
-  url? : string
-  data? : any
-  kgID? : string
-  targetParcellation : string
-  properties : any
+  name: string
+  absolutePath: string
+  byteSize: number
+  contentType: string
+}
+
+export interface FileSupplementData{
+  data: any
 }
 
 export interface Property{
@@ -401,8 +423,9 @@ export interface Property{
 }
 
 export interface Publication{
+  name: string
   doi : string
-  citation : string
+  cite : string
 }
 
 export interface UIStateInterface{
@@ -454,4 +477,12 @@ export function isDefined(obj){
 export const exportedStates = {
   pluginState,
   viewerConfigState
+}
+
+export interface ParcellationRegion {
+  name: string
+}
+
+export interface ReferenceSpace {
+  name: string
 }
\ No newline at end of file
diff --git a/src/ui/databrowser/databrowser.component.ts b/src/ui/databrowser/databrowser.component.ts
index 003a019511c6addb57fb61d34bca3adcfe891ab8..bee9c53cf554c960d200b4d33d0e0dc657572ef5 100644
--- a/src/ui/databrowser/databrowser.component.ts
+++ b/src/ui/databrowser/databrowser.component.ts
@@ -3,7 +3,6 @@ import { Store, select } from "@ngrx/store";
 import { DataStateInterface, Property, safeFilter, DataEntry, File, SELECT_REGIONS, getLabelIndexMap, isDefined, SPATIAL_GOTO_PAGE, CHANGE_NAVIGATION, UPDATE_SPATIAL_DATA_VISIBLE, DESELECT_REGIONS, DESELECT_LANDMARKS, SELECT_LANDMARKS } from "../../services/stateStore.service";
 import { map, filter, distinctUntilChanged } from "rxjs/operators";
 import { HasPathProperty } from "../../util/pipes/pathToNestedChildren.pipe";
-import { TreeComponent } from "../../components/tree/tree.component";
 import { Observable, Subscription, combineLatest } from "rxjs";
 import { FileViewer } from "../fileviewer/fileviewer.component";
 import { WidgetServices } from "../../atlasViewer/widgetUnit/widgetService.service";
@@ -21,7 +20,7 @@ export class DataBrowserUI implements OnDestroy,OnInit{
 
   private fileViewerComponentFactory : ComponentFactory<FileViewer>
 
-  hitsPerPage : number = 15
+  hitsPerPage : number = 5
   currentPage :  number = 0
 
   metadataMap : Map<string,Map<string,{properties:Property}>>
@@ -42,7 +41,7 @@ export class DataBrowserUI implements OnDestroy,OnInit{
   public selectedPOI$ : Observable<any[]>
 
   private metadataMap$ : Observable<any>
-  private fetchedDataEntries$ : Observable<any>
+  public fetchedDataEntries$ : Observable<any>
   private selectParcellation$ : Observable<any>
   private dedicatedViewString$ : Observable<string|null>
   private spatialDataEntries$ : Observable<any[]>
@@ -50,6 +49,14 @@ export class DataBrowserUI implements OnDestroy,OnInit{
 
   private subscriptions : Subscription[] = []
 
+  get showDataTypes(){
+    const availableDatatypes = new Set(this.dataEntries
+      .map(de => de.formats)
+      .reduce((acc, item) => acc.concat(item), [])
+      .filter(type => !this.hideDataTypes.has(type)))
+    return availableDatatypes
+  }
+
   constructor(
     private cfr : ComponentFactoryResolver,
     private store : Store<DataStateInterface>,
@@ -162,6 +169,13 @@ export class DataBrowserUI implements OnDestroy,OnInit{
     return this.constantService.spatialResultsPerPage
   }
 
+  deselectRegion(region:any){
+    this.store.dispatch({
+      type: DESELECT_REGIONS,
+      deselectRegions: [region]
+    })
+  }
+
   toggleSpatialDataVisible(){
     this.store.dispatch({
       type : UPDATE_SPATIAL_DATA_VISIBLE,
@@ -226,8 +240,7 @@ export class DataBrowserUI implements OnDestroy,OnInit{
 
   handleFlatTreeNodeClick(payload:{dataset:DataEntry, file:File}){
     const { dataset, file } = payload
-    const { properties, kgID } = dataset
-    if(file.mimetype){
+    if(dataset.formats.findIndex(format => format.toLowerCase() === 'nifti' ) >= 0){
 
       // TODO use KG id in future
       if(this.dataWindowRegistry.has(file.name)){
@@ -238,7 +251,7 @@ export class DataBrowserUI implements OnDestroy,OnInit{
       this.dataWindowRegistry.add(file.name)
 
       const component = this.fileViewerComponentFactory.create(this.injector)
-      component.instance.searchResultFile = Object.assign({}, file, { datasetProperties : properties }, kgID ? { kgID } : {})
+      component.instance.searchResultFile = file
       const compref = this.widgetServices.addNewWidget(component,{title:file.name,exitable:true,state:'floating'})
 
       /* on destroy, removes name from registry */
diff --git a/src/ui/databrowser/databrowser.template.html b/src/ui/databrowser/databrowser.template.html
index 9a5460f8191ab97f83314fb340924c05cc929359..c03af707c259dd6d9d83ac971355e334422384ea 100644
--- a/src/ui/databrowser/databrowser.template.html
+++ b/src/ui/databrowser/databrowser.template.html
@@ -1,23 +1,10 @@
-<!-- Header -->
-<div *ngIf = "selectedPOI$ | async" databrowserheader>
-  <span>
-    {{ !(selectedPOI$ | async) ? '' : (((selectedPOI$ | async).length === 0 ? 'No' : (selectedPOI$ | async).length) + ' selected region' + ((selectedPOI$ | async).length > 1 ? 's' : '')) + ' of interest'  }} 
-  </span>
-  <small
-    *ngIf = "(selectedPOI$ | async).length > 0"
-    class = "btn btn-link"
-    (click) = "clearAllPOIs()">
-    clear all
-  </small>
-</div>
-
 <!-- Filter -->
 <div filterBlock>
   <div>
-    Filter
+    Filter {{ dataEntries.length }}
   </div>
   <div
-    *ngFor = "let type of dataEntries | getUniqueProperty : 'type' "
+    *ngFor = "let type of dataEntries | getPropMapPipe : 'formats' | flatmapArrayPipe | getUniquePipe "
     class = "clickable"
     (click)="toggleTypeVisibility(type)">
     <small>
@@ -45,10 +32,20 @@
       Spatial Search
     </small>
   </div>
+
+  <pill-component
+    [containerStyle]="{backgroundColor:'rgba(128,128,128,0.2)'}"
+    [closeBtnStyle]="{backgroundColor:'rgba(128,128,128,0.5)'}"
+    (closeClicked)="deselectRegion(region)"
+    [title]="region.name"
+    *ngFor="let region of selectedRegions$ | async">
+  </pill-component>
 </div>
 
 <!-- Data -->
-<div *ngIf = "spatialDataVisible && false">
+
+<!-- spatial search -->
+<div *ngIf = "false && spatialDataVisible">
   <panel-component [collapseBody] = "true" [bodyCollapsable] = "true">
     <div heading>
       <span>
@@ -79,8 +76,22 @@
     </div>
   </panel-component>
 </div>
+
+<!-- other data -->
+<pagination-component
+  (paginationChange)="currentPage = $event"
+  [hitsPerPage]="hitsPerPage"
+  [total]="(fetchedDataEntries$ | async | filterDataEntriesByType : showDataTypes | filterDataEntriesByRegion : (selectedRegions$ | async)).length"
+  [currentPage]="currentPage">
+</pagination-component>
+<dataset-viewer
+  *ngFor="let dataset of fetchedDataEntries$ | async | filterDataEntriesByType : showDataTypes | filterDataEntriesByRegion : (selectedRegions$ | async) | searchResultPagination : currentPage : hitsPerPage"
+  (launchFileViewer) = "handleFlatTreeNodeClick($event)"
+  [dataset] = "dataset">
+
+</dataset-viewer>
 <div 
-  *ngIf = "(selectedPOI$ | async) && (selectedPOI$ | async).length > 0; else noSelectedRegion"
+  *ngIf = "false && (selectedPOI$ | async) && (selectedPOI$ | async).length > 0"
   regionsContainer>
 
   <div
@@ -89,7 +100,7 @@
     <panel-component 
       [collapseBody] = "true"
       [bodyCollapsable] = "true">
-      <div [ngClass] = "(data.searchResults | filterDataEntriesByType : hideDataTypes).length === 0 ? 'noResultClass' : ''" 
+      <div [ngClass] = "(data.searchResults | filterDataEntriesByType : showDataTypes).length === 0 ? 'noResultClass' : ''" 
         displayflex
         heading>
         <div maintext>
diff --git a/src/ui/datasetViewer/datasetViewer.style.css b/src/ui/datasetViewer/datasetViewer.style.css
index f95c2e97aa13bcc73d1324e153874bd4cdb2a063..5c38860fd0db7140609c87ab55fb6039de22f32c 100644
--- a/src/ui/datasetViewer/datasetViewer.style.css
+++ b/src/ui/datasetViewer/datasetViewer.style.css
@@ -7,4 +7,9 @@ flat-tree-component
 :host-context([darktheme="true"]) hr
 {
   border-color: rgba(0, 0, 0, 0.5);
+}
+
+.dataset-pill
+{
+  font-size:80%;
 }
\ No newline at end of file
diff --git a/src/ui/datasetViewer/datasetViewer.template.html b/src/ui/datasetViewer/datasetViewer.template.html
index f14ab264aefd475ae2ab257a599416a0f7b8631d..829c6ceee8a7725e876ba7a2906b06aa1d0b998f 100644
--- a/src/ui/datasetViewer/datasetViewer.template.html
+++ b/src/ui/datasetViewer/datasetViewer.template.html
@@ -1,30 +1,39 @@
 <div *ngIf = "dataset; else defaultDisplay">
+
+  <pill-component
+    class="dataset-pill"
+    [title]="format"
+    [showClose]="false"
+    *ngFor="let format of dataset.formats">
+
+  </pill-component>
+  
   <h4 title>
     {{ dataset.name }}
   </h4>
-  <kg-entry-viewer *ngIf = "dataset.kgID; else noKgID" [kgQueryString] = "dataset.kgID">
+  <kg-entry-viewer [dataset]="dataset">
 
   </kg-entry-viewer>
 
-  <hr />
-  <h5>
-    Preview Dataset
-  </h5>
-  <flat-tree-component
-    #flatTreeNode
-    *ngFor = "let item of dataset.files | copyProperty : 'filename' : 'path' | pathToNestedChildren"
-    [childrenExpanded] = "false"
-    [renderNode] = "renderNode"
-    [inputItem] = " item "
-    (treeNodeClick)= "previewFileClick($event, flatTreeNode)">
+  <div *ngIf="false">
 
-  </flat-tree-component>
-  <hr />
+      <hr />
+      <h5>
+        Preview Dataset
+      </h5>
+      <flat-tree-component
+        #flatTreeNode
+        *ngFor = "let item of dataset.files | copyProperty : 'filename' : 'path' | pathToNestedChildren"
+        [childrenExpanded] = "false"
+        [renderNode] = "renderNode"
+        [inputItem] = " item "
+        (treeNodeClick)= "previewFileClick($event, flatTreeNode)">
+    
+      </flat-tree-component>
+      <hr />
+  </div>
 </div>
 
 <ng-template #defaultDisplay>
   Nothing to display ...
 </ng-template>
-
-<ng-template #noKgID>
-</ng-template>
diff --git a/src/ui/fileviewer/dedicated/dedicated.component.ts b/src/ui/fileviewer/dedicated/dedicated.component.ts
index 201f6d3914a9c698c15246fedf91fb54183c0743..41eafd3a5cf161471c493765584a24d262c4f5e7 100644
--- a/src/ui/fileviewer/dedicated/dedicated.component.ts
+++ b/src/ui/fileviewer/dedicated/dedicated.component.ts
@@ -33,7 +33,7 @@ export class DedicatedViewer implements OnDestroy{
   }
 
   get isShowing(){
-    return this.ngLayers.has(`nifti://${this.searchResultFile.url}`)
+    return this.ngLayers.has(`nifti://${this.searchResultFile.absolutePath}`)
   }
 
   ngOnDestroy(){
@@ -44,8 +44,8 @@ export class DedicatedViewer implements OnDestroy{
     this.store.dispatch({
       type : ADD_NG_LAYER,
       layer : {
-        name : this.searchResultFile.url,
-        source : `nifti://${this.searchResultFile.url}`,
+        name : this.searchResultFile.absolutePath,
+        source : `nifti://${this.searchResultFile.absolutePath}`,
         mixability : 'nonmixable',
         shader : getActiveColorMapFragmentMain()
       }
@@ -62,7 +62,7 @@ export class DedicatedViewer implements OnDestroy{
     this.store.dispatch({
       type : REMOVE_NG_LAYER,
       layer : {
-        name : this.searchResultFile.url
+        name : this.searchResultFile.absolutePath
       }
     })
   }
diff --git a/src/ui/fileviewer/fileviewer.component.ts b/src/ui/fileviewer/fileviewer.component.ts
index 7ad43ca02cf943a4b2bb75df913c7683f45c925e..8de2dc462d592923183553960514a4c21574e843 100644
--- a/src/ui/fileviewer/fileviewer.component.ts
+++ b/src/ui/fileviewer/fileviewer.component.ts
@@ -1,7 +1,7 @@
 import { Component, Input, OnChanges, OnDestroy, ViewChild, ElementRef, OnInit, Output, EventEmitter } from '@angular/core'
 
 import { DomSanitizer } from '@angular/platform-browser';
-import { File } from '../../services/stateStore.service';
+import { File, FileSupplementData } from '../../services/stateStore.service';
 import { interval,from } from 'rxjs';
 import { switchMap,take,retry } from 'rxjs/operators'
 
@@ -14,7 +14,14 @@ import { switchMap,take,retry } from 'rxjs/operators'
 })
 
 export class FileViewer implements OnChanges,OnDestroy,OnInit{
+  /**
+   * fetched directly from KG
+   */
   @Input() searchResultFile : File
+  /**
+   * currently going to have to be application specific
+   */
+  @Input() fileSupplement: FileSupplementData
   
   @ViewChild('childChart') childChart : ChartComponentInterface
 
@@ -39,8 +46,8 @@ export class FileViewer implements OnChanges,OnDestroy,OnInit{
   }
 
   get downloadUrl(){
-    return this.searchResultFile.url ? 
-      this.searchResultFile.url : 
+    return this.searchResultFile.absolutePath ? 
+      this.searchResultFile.absolutePath : 
       this._downloadUrl ? 
         this.sanitizer.bypassSecurityTrustResourceUrl(this._downloadUrl)  :
         null
@@ -69,8 +76,8 @@ export class FileViewer implements OnChanges,OnDestroy,OnInit{
     },(err)=>console.warn('warning',err))
 
 
-    if(!this.searchResultFile.url && this.searchResultFile.data){
-      const stringJson = JSON.stringify(this.searchResultFile.data)
+    if(!this.searchResultFile.absolutePath && this.fileSupplement.data){
+      const stringJson = JSON.stringify(this.fileSupplement.data)
       const newBlob = new Blob([stringJson],{type:'application/octet-stream'})
       this._downloadUrl = URL.createObjectURL(newBlob)
     }
@@ -86,7 +93,7 @@ export class FileViewer implements OnChanges,OnDestroy,OnInit{
   }
 
   get downloadName(){
-    return this.searchResultFile.filename
+    return this.searchResultFile.name
   }
 
   get downloadPng(){
diff --git a/src/ui/fileviewer/fileviewer.template.html b/src/ui/fileviewer/fileviewer.template.html
index 09221233f9181b8603c55ad3993216cf1adf7135..c99d9346670984df61250ba1a7fcc65df96820b0 100644
--- a/src/ui/fileviewer/fileviewer.template.html
+++ b/src/ui/fileviewer/fileviewer.template.html
@@ -3,20 +3,15 @@
 </div>
 
 <!-- KG Entry Viewer -->
-<kg-entry-viewer *ngIf = "searchResultFile.kgID && false" [kgQueryString] = "searchResultFile.kgID">
-
-</kg-entry-viewer>
+<!-- <kg-entry-viewer *ngIf = "searchResultFile.kgID && false" [dataset] = "searchResultFile">
+</kg-entry-viewer> -->
 
 <!-- citation -->
-<div style="margin:1em" *ngIf="searchResultFile && !searchResultFile.kgID && searchResultFile.properties && searchResultFile.properties.publications && searchResultFile.properties.publications.length > 0">
-  <h5>
-    Citations for this dataset:
-  </h5>
-  <citations-component 
-    citationContainer
-    [properties] = "searchResultFile.properties">
-  </citations-component>
-</div>
+<!-- <citations-component 
+  citationContainer
+  *ngIf = "searchResultFile && !searchResultFile.kgID"
+  [properties] = "searchResultFile.datasetProperties">
+</citations-component> -->
 
 <!-- file viewer -->
 <div 
@@ -82,11 +77,11 @@
 </div>
 
 <!-- caption -->
-<readmore-component *ngIf = "searchResultFile.properties && searchResultFile.properties.description">
+<!-- <readmore-component *ngIf = "searchResultFile.properties && searchResultFile.properties.description">
   <small id = "captions">
     {{ searchResultFile.properties.description }}
   </small>
-</readmore-component>
+</readmore-component> -->
 
 <div anchorContainer *ngIf = "downloadUrl">
   <a [href]="downloadUrl" target = "_blank" download>Download File</a>
diff --git a/src/ui/kgEntryViewer/kgentry.component.ts b/src/ui/kgEntryViewer/kgentry.component.ts
index bb01d8c7d4a71b1e52e40a5c011226dc5e0d58aa..df948f272a2e3b5f75fd51059ae31b785d032c53 100644
--- a/src/ui/kgEntryViewer/kgentry.component.ts
+++ b/src/ui/kgEntryViewer/kgentry.component.ts
@@ -1,4 +1,5 @@
-import { Component, Input, OnInit } from "@angular/core";
+import { Component, Input } from "@angular/core";
+import { DataEntry } from "src/services/stateStore.service";
 
 @Component({
   selector : 'kg-entry-viewer',
@@ -8,34 +9,12 @@ import { Component, Input, OnInit } from "@angular/core";
   ]
 })
 
-export class KgEntryViewer implements OnInit{
-  @Input() kgQueryString : string = null
+export class KgEntryViewer {
+  @Input() dataset: DataEntry
 
   public kgData : any = null
   public kgError : any = null
 
-  ngOnInit(){
-    if(this.kgQueryString){
-      fetch(`${KGROOT}${this.kgQueryString}`)
-        .then(res => res.json())
-        .then(json => {
-          if(json.found)
-            return json._source
-          else
-            throw new Error('No documents were found.')
-        })
-        .then(json => this.kgData = json)
-        .catch(e => {
-          console.error('fetching KG data error', e)
-          this.kgData = null
-          this.kgError = JSON.stringify(e)
-        })
-    }else{
-      console.error('kgQueryString empty!')
-      this.kgError = 'Knowledge Graph ID empty'
-    }
-  }
-
   get tableColClass1(){
     return `col-xs-4 col-lg-4 tableEntry`
   }
@@ -44,13 +23,7 @@ export class KgEntryViewer implements OnInit{
     return `col-xs-8 col-lg-8 tableEntry`
   }
 
-  get kgHref(){
-    return `https://kg.humanbrainproject.org/webapp/#${this.kgQueryString}`
-  }
-
   public isArray(v){
     return v.constructor === Array
   }
 }
-
-const KGROOT = `https://kg.humanbrainproject.org/proxy/default/kg/`
\ No newline at end of file
diff --git a/src/ui/kgEntryViewer/kgentry.style.css b/src/ui/kgEntryViewer/kgentry.style.css
index 08aa2ff604ef4cb81be1dbfaf936c5df17aff5c5..4ac3fc6f4bd8f118c0339fff562389ee4d18239c 100644
--- a/src/ui/kgEntryViewer/kgentry.style.css
+++ b/src/ui/kgEntryViewer/kgentry.style.css
@@ -22,9 +22,13 @@ div[container]
   overflow:hidden;
 }
 
-a[linkToKG]
+a[link]
 {
   display: inline-block;
   margin-top: 1rem;
-  white-space: nowrap;
+}
+
+a[link]:hover
+{
+  text-decoration: none;
 }
\ No newline at end of file
diff --git a/src/ui/kgEntryViewer/kgentry.template.html b/src/ui/kgEntryViewer/kgentry.template.html
index 8f7e85d366d02bd8addaa6f050a281a9b599b9bd..5986ebf305f5708d3f0a02f4c0600f2d14eedff9 100644
--- a/src/ui/kgEntryViewer/kgentry.template.html
+++ b/src/ui/kgEntryViewer/kgentry.template.html
@@ -1,151 +1,84 @@
-<div *ngIf = "kgData; else showDefault" container>
+<div *ngIf="dataset" container>
 
+  <!-- description -->
   <readmore-component>
-
-    <panel-component *ngIf = "false" [collapseBody] = "true" [bodyCollapsable] = "true">
-      <div heading>
-        Description
-      </div>
-      <div body>
-        {{ kgData.description.value }}
-      </div>
-    </panel-component>
-
-    <panel-component *ngIf = "false"  [collapseBody] = "true" [bodyCollapsable] = "true">
-      <div heading>
-        Project
-      </div>
-      <div body>
-        {{ kgData.component.value }}
-      </div>
-    </panel-component>
-
-    <panel-component *ngIf = "false"  [collapseBody] = "true" [bodyCollapsable] = "true">
-      <div heading>
-        Contributor(s)
-      </div>
-      <div body>
-        <!-- TODO maybe object instead of array -->
-        <div *ngFor = "let contributor of kgData.contributors">
-          {{ contributor.value }}
-        </div>
-      </div>
-    </panel-component>
-
-    <panel-component *ngIf = "false"  [collapseBody] = "true" [bodyCollapsable] = "true">
-      <div heading>
-        Custodian(s)
-      </div>
-      <div body>
-        <!-- TODO Maybe array -->
-        {{ kgData.owners.value }}
-      </div>
-    </panel-component>
-
-    <panel-component *ngIf = "kgData.publications" [collapseBody] = "true" [bodyCollapsable] = "true">
-      <div heading>
-        Related Publication(s)
-      </div>
-      <div body>
-        <div *ngIf = "isArray(kgData.publications); else singlePublicationTemplate">
-          <div publicationContainer *ngFor = "let publication of kgData.publications">
-            {{ publication.value.split('\n')[0] }}
-          </div>
-        </div>
-        <ng-template #singlePublicationTemplate>
-          <div publicationContainer>
-            {{ kgData.publications.value.split('\n')[0] }}
-          </div>
-        </ng-template>
-      </div>
-    </panel-component>
-
-    <panel-component *ngIf = "false"  [collapseBody] = "true" [bodyCollapsable] = "true">
-      <div heading>
-        Brain atlas
-      </div>
-      <div body>
-        {{ kgData.atlas.value }}
-      </div>
-    </panel-component>
-
-    <panel-component *ngIf = "kgData.preparation" [collapseBody] = "true" [bodyCollapsable] = "true">
-      <div heading>
-        Preparation
-      </div>
-      <div body>
-        {{ kgData.preparation.value }}
-      </div>
-    </panel-component>
-
-    <panel-component *ngIf = "kgData.methods" [collapseBody] = "true" [bodyCollapsable] = "true">
-      <div heading>
-        Methods
-      </div>
-      <div body>
-        <div *ngIf = "isArray(kgData.methods); else singleMethodTemplate">
-          <div *ngFor = "let method of kgData.methods">
-            {{ method.value }}
-          </div>
-        </div>
-        <ng-template #singleMethodTemplate>
-          {{ kgData.methods.value }}
-        </ng-template>
-      </div>
-    </panel-component>
-
-    <panel-component *ngIf = "kgData.license_info" [collapseBody] = "true" [bodyCollapsable] = "true">
-      <div heading>
-        License
-      </div>
-      <div body>
-        {{ kgData.license_info.value }}
-      </div>
-    </panel-component>
-
-    <panel-component *ngIf = "kgData.files" [collapseBody] = "true" [bodyCollapsable] = "true">
-      <div heading>
-        Files
-      </div>
-      <div body>
-        <div *ngIf = "isArray(kgData.files);else singleFileTemplate">
-          <div *ngFor = "let file of kgData.files">
-            {{ file.value }}
-          </div>
-        </div>
-        <ng-template #singleFileTemplate>
-          {{ kgData.files.value }}
-        </ng-template>
-      </div>
-    </panel-component>
-
-    <panel-component *ngIf = "kgData.subjects" [collapseBody] = "true" [bodyCollapsable] = "true">
-      <div heading>
-        Subjects
-      </div>
-      <div body>
-        <kg-entry-viewer-subject-viewer
-          [subjects] = "kgData.subjects">
-
-        </kg-entry-viewer-subject-viewer>
-      </div>
-    </panel-component>
-
+    {{ dataset.description }}
   </readmore-component>
-  <a target = "_blank" [href] = "kgHref" linkToKG>
-    Open in Knowledge Graph <i class = "glyphicon glyphicon-new-window"></i>
-  </a>
 
-</div>
-<ng-template #showDefault>
-  <div reportError *ngIf = "kgError">
-    Fetching metadata from the Knowledge Graph failed - {{ kgError }}
-  </div>
-  <div *ngIf = "!kgError">
-    Fetching KG Data 
+  <!-- other data -->
+
+  <panel-component *ngIf = "false"  [collapseBody] = "true" [bodyCollapsable] = "true">
+    <div heading>
+      Contributor(s)
+    </div>
+    <div body>
+      <!-- TODO maybe object instead of array -->
+      <div *ngFor = "let contributor of dataset.contributors">
+        {{ contributor.value }}
+      </div>
+    </div>
+  </panel-component>
+
+  <panel-component [collapseBody] = "true" [bodyCollapsable] = "true">
+    <div heading>
+      Custodian(s)
+    </div>
+    <div body>
+      <!-- TODO Maybe array -->
+      <div *ngFor="let custodian of dataset.custodians">
+        {{ custodian }}
+      </div>
+    </div>
+  </panel-component>
+
+  <panel-component *ngIf = "dataset.publications" [collapseBody] = "true" [bodyCollapsable] = "true">
+    <div heading>
+      Related Publication(s)
+    </div>
+    <div body>
+      <div *ngFor="let publication of dataset.publications">
+        <a target="_blank" link [href]="'https://doi.org/' + publication.doi">
+          {{ publication.cite }}
+          <i class = "glyphicon glyphicon-new-window"></i>
+        </a>
+      </div>
+    </div>
+  </panel-component>
+
+  <panel-component *ngIf = "dataset.licenseInfo || dataset.license" [collapseBody] = "true" [bodyCollapsable] = "true">
+    <div heading>
+      License
+    </div>
+    <div body>
+      <div *ngFor="let l of dataset.licence">
+        {{ l }}
+      </div>
+      <div *ngFor="let l of dataset.licenseInfo">
+        {{ l }}
+      </div>
+    </div>
+  </panel-component>
+
+  <panel-component *ngIf = "dataset.files" [collapseBody] = "true" [bodyCollapsable] = "true">
+    <div heading>
+      Files
+    </div>
+    <div body>
+      <div *ngFor="let file of dataset.files">
+        <a link target="_blank" [href]="file.absolutePath">
+          {{ file.name }}
+          <i class="glyphicon glyphicon-download-alt"></i>
+        </a>
+      </div>
+    </div>
+  </panel-component>
+
+  <a
+    *ngFor="let ref of dataset.kgReference"
+    [href]="'https://doi.org/' + ref"
+    target="_blank">
+    Open in Knowledge Graph
+    <i class = "glyphicon glyphicon-new-window"></i>
+  </a>
 
-    <span class = "homeAnimationDots loadingAnimationDots">&bull;</span>
-    <span class = "homeAnimationDots loadingAnimationDots">&bull;</span>
-    <span class = "homeAnimationDots loadingAnimationDots">&bull;</span>
-  </div>
-</ng-template>
\ No newline at end of file
+</div>
\ No newline at end of file
diff --git a/src/ui/ui.module.ts b/src/ui/ui.module.ts
index e744af52480e14be9a7e051cc199042cb7568482..aa4d5a44013be709d12558842f2f43535d210566 100644
--- a/src/ui/ui.module.ts
+++ b/src/ui/ui.module.ts
@@ -17,7 +17,9 @@ import { RadarChart } from "./fileviewer/radar/radar.chart.component";
 import { LineChart } from "./fileviewer/line/line.chart.component";
 import { PathToNestedChildren } from "../util/pipes/pathToNestedChildren.pipe";
 import { CopyPropertyPipe } from "../util/pipes/copyProperty.pipe";
-import { GetUniqueProperty } from "../util/pipes/getUniqueProperty.pipe";
+import { GetPropMapPipe } from "../util/pipes/getPropMap.pipe";
+import { GetUniquePipe } from "src/util/pipes/getUnique.pipe";
+
 import { FilterDataEntriesbyType } from "../util/pipes/filterDataEntriesByType.pipe";
 import { DedicatedViewer } from "./fileviewer/dedicated/dedicated.component";
 import { LandmarkUnit } from "./nehubaContainer/landmarkUnit/landmarkUnit.component";
@@ -41,6 +43,8 @@ import { FilterNullPipe } from "../util/pipes/filterNull.pipe";
 import { ShowToastDirective } from "../util/directives/showToast.directive";
 import { HelpComponent } from "./help/help.component";
 import { ConfigComponent } from './config/config.component'
+import { FlatmapArrayPipe } from "src/util/pipes/flatMapArray.pipe";
+import { FilterDataEntriesByRegion } from "src/util/pipes/filterDataEntriesByRegion.pipe";
 
 
 @NgModule({
@@ -81,8 +85,11 @@ import { ConfigComponent } from './config/config.component'
     filterRegionDataEntries,
     PathToNestedChildren,
     CopyPropertyPipe,
-    GetUniqueProperty,
+    GetPropMapPipe,
+    GetUniquePipe,
+    FlatmapArrayPipe,
     FilterDataEntriesbyType,
+    FilterDataEntriesByRegion,
     SafeStylePipe,
     GetLayerNameFromDatasets,
     SortDataEntriesToRegion,
diff --git a/src/util/pipes/filterDataEntriesByRegion.pipe.ts b/src/util/pipes/filterDataEntriesByRegion.pipe.ts
new file mode 100644
index 0000000000000000000000000000000000000000..9236d20bd695bc7e59e55a52cc3265febe7122d7
--- /dev/null
+++ b/src/util/pipes/filterDataEntriesByRegion.pipe.ts
@@ -0,0 +1,27 @@
+import { Pipe, PipeTransform } from "@angular/core";
+import { DataEntry } from "src/services/stateStore.service";
+
+@Pipe({
+  name: 'filterDataEntriesByRegion'
+})
+
+export class FilterDataEntriesByRegion implements PipeTransform{
+  public transform(dataentries: DataEntry[], selectedRegions: any[]) {
+    return selectedRegions.length > 0
+      ? dataentries.filter(de => 
+          de.parcellationRegion.some(pr => {
+
+            /**
+             * TODO: temporary hack, some dataset region name is not exactly the same as region
+             */
+            const regex = new RegExp(pr.name)
+            return selectedRegions.some(sr => regex.test(sr.name))
+            /**
+             * more correct
+             */
+            return selectedRegions.some(sr => sr.name === pr.name)
+          })
+        )
+      : dataentries
+  }
+}
\ No newline at end of file
diff --git a/src/util/pipes/filterDataEntriesByType.pipe.ts b/src/util/pipes/filterDataEntriesByType.pipe.ts
index f343173f3d1261e3f8ddd933bc481ace5452df46..0bc735f3cfffbd24babd23e43457318873c9f109 100644
--- a/src/util/pipes/filterDataEntriesByType.pipe.ts
+++ b/src/util/pipes/filterDataEntriesByType.pipe.ts
@@ -7,7 +7,7 @@ import { DataEntry } from "../../services/stateStore.service";
 })
 
 export class FilterDataEntriesbyType implements PipeTransform{
-  public transform(dataEntries:DataEntry[],hideTypeSet:Set<string>):DataEntry[]{
-    return dataEntries.filter(dataEntry=>!hideTypeSet.has(dataEntry.type))
+  public transform(dataEntries:DataEntry[],showDataType:Set<string>):DataEntry[]{
+    return dataEntries.filter(dataEntry=>dataEntry.formats.some(format => showDataType.has(format)))
   }
 }
\ No newline at end of file
diff --git a/src/util/pipes/flatMapArray.pipe.ts b/src/util/pipes/flatMapArray.pipe.ts
new file mode 100644
index 0000000000000000000000000000000000000000..1b5d62f0dada9b7048d2d866b8a4cca54525b124
--- /dev/null
+++ b/src/util/pipes/flatMapArray.pipe.ts
@@ -0,0 +1,11 @@
+import { Pipe, PipeTransform } from "@angular/core";
+
+@Pipe({
+  name: 'flatmapArrayPipe'
+})
+
+export class FlatmapArrayPipe implements PipeTransform{
+  public transform(aoa: any[][]){
+    return aoa.reduce((acc, array) => acc.concat(array), [])
+  }
+}
\ No newline at end of file
diff --git a/src/util/pipes/getPropMap.pipe.ts b/src/util/pipes/getPropMap.pipe.ts
new file mode 100644
index 0000000000000000000000000000000000000000..a761b1d7a67707a58b5588158dc2b86817bbf93b
--- /dev/null
+++ b/src/util/pipes/getPropMap.pipe.ts
@@ -0,0 +1,16 @@
+import { Pipe, PipeTransform } from "@angular/core";
+
+/**
+ * nb, will return undefined elements
+ * nb, will throw error if one of the input element is not an object
+ */
+
+@Pipe({
+  name : 'getPropMapPipe'
+})
+
+export class GetPropMapPipe implements PipeTransform{
+  public transform(arr:any[],prop:string):any[]{
+    return arr.map(item => item[prop])
+  }
+}
\ No newline at end of file
diff --git a/src/util/pipes/getUnique.pipe.ts b/src/util/pipes/getUnique.pipe.ts
new file mode 100644
index 0000000000000000000000000000000000000000..1ab3800b61ac9f4d7c12390b575523170fee4850
--- /dev/null
+++ b/src/util/pipes/getUnique.pipe.ts
@@ -0,0 +1,12 @@
+import { Pipe, PipeTransform } from "@angular/core";
+
+
+@Pipe({
+  name: 'getUniquePipe'
+})
+
+export class GetUniquePipe implements PipeTransform{
+  public transform(arr: any[]) {
+    return Array.from(new Set(arr))
+  }
+}
\ No newline at end of file
diff --git a/src/util/pipes/getUniqueProperty.pipe.ts b/src/util/pipes/getUniqueProperty.pipe.ts
deleted file mode 100644
index b7754ccaace64af70eebc8eef558f0a259ba4841..0000000000000000000000000000000000000000
--- a/src/util/pipes/getUniqueProperty.pipe.ts
+++ /dev/null
@@ -1,18 +0,0 @@
-import { Pipe, PipeTransform } from "@angular/core";
-
-
-@Pipe({
-  name : 'getUniqueProperty'
-})
-
-export class GetUniqueProperty implements PipeTransform{
-  public transform(arr:any[],prop:string):string[]{
-    return [...arr.reduce((acc:Set<string>,curr)=>{
-      return curr[prop] && typeof curr[prop] === 'string' ? 
-        acc.has(curr[prop]) ?
-          acc :
-          acc.add(curr[prop]) :
-        acc
-    },new Set())]
-  }
-}
\ No newline at end of file
diff --git a/src/util/pipes/groupDataEntriesByRegion.pipe.ts b/src/util/pipes/groupDataEntriesByRegion.pipe.ts
index 7c2986db80ad5ebb4152f332f70aa402473cf3be..6778b49808d0483a0a357ae417d5cbf89ae794ae 100644
--- a/src/util/pipes/groupDataEntriesByRegion.pipe.ts
+++ b/src/util/pipes/groupDataEntriesByRegion.pipe.ts
@@ -9,18 +9,18 @@ export class GroupDatasetByRegion implements PipeTransform{
   {
     
     return datasets.reduce((acc,curr)=>{
-      return (curr.regionName && curr.regionName.length > 0)
-        ? curr.regionName.reduce((acc2,reName)=>{
+      return (curr.parcellationRegion && curr.parcellationRegion.length > 0)
+        ? curr.parcellationRegion.reduce((acc2,reName)=>{
           const idx = acc.findIndex(it => it.region === null 
-            ? reName.regionName === 'none' 
-            : it.region.name === reName.regionName )
+            ? reName.name === 'none' 
+            : it.region.name === reName.name )
 
           return idx >= 0
             ? acc2.map((v,i)=> i === idx 
               ? Object.assign({},v,{searchResults : v.searchResults.concat(curr)}) 
               : v ) 
             : acc2.concat({
-                region : this.getRegionFromRegionName(reName.regionName, regions),
+                region : this.getRegionFromRegionName(reName.name, regions),
                 searchResults : [ curr ]
               })
           },acc)
diff --git a/src/util/pipes/sortDataEntriesIntoRegion.pipe.ts b/src/util/pipes/sortDataEntriesIntoRegion.pipe.ts
index 6a32f88ac7e132d9ac74c8f7c09d61f5eea2d9f8..7f2393f94269caa3fc760c50fb025f69dbb47ba3 100644
--- a/src/util/pipes/sortDataEntriesIntoRegion.pipe.ts
+++ b/src/util/pipes/sortDataEntriesIntoRegion.pipe.ts
@@ -9,7 +9,7 @@ export class SortDataEntriesToRegion implements PipeTransform{
   public transform(regions: any[], datasets:DataEntry[]):{region:any,searchResults:DataEntry[]}[]{
     return regions.map(region => ({
       region,
-      searchResults : datasets.filter(dataset => dataset.regionName.some(r => r.regionName === region.name))
+      searchResults : datasets.filter(dataset => dataset.parcellationRegion.some(r => r.name === region.name))
     }))
   }
 }
\ No newline at end of file
diff --git a/typings/index.d.ts b/typings/index.d.ts
index cc355ad130d56514f9e956fa79c45c19870c0a6e..4007a30c18e11c74bc2854ad9eff4e621525379a 100644
--- a/typings/index.d.ts
+++ b/typings/index.d.ts
@@ -11,4 +11,5 @@ declare module '*.css' {
 declare var PLUGINDEV : string
 declare var BUNDLEDPLUGINS : string[]
 declare var VERSION : string
-declare var PRODUCTION: boolean
\ No newline at end of file
+declare var PRODUCTION: boolean
+declare var BACKEND_URL: string
\ No newline at end of file
diff --git a/webpack.staticassets.js b/webpack.staticassets.js
index de19c73b0e9955a1f4f4ab164bc976ea4ba00771..6523e83f2a2128ce581bfaaac5f0755308807f92 100644
--- a/webpack.staticassets.js
+++ b/webpack.staticassets.js
@@ -54,7 +54,8 @@ module.exports = {
           : JSON.stringify('unspecificied hash'),
       PRODUCTION: process.env.PRODUCTION
         ? true
-        : false
+        : false,
+      BACKEND_URL: JSON.stringify(process.env.BACKEND_URL || 'http://localhost:3000/')
     })
     // ...ignoreArr.map(dirname => new webpack.IgnorePlugin(/\.\/plugin_examples/))
   ]