From 1597835a019c7e17a128542a4046d67e655b2b52 Mon Sep 17 00:00:00 2001
From: Maximilian Schmidt <max.schmidt@fz-juelich.de>
Date: Fri, 25 May 2018 18:12:50 +0900
Subject: [PATCH] Add script to run network simulations
---
.../run_network_simulations.py | 141 ++++++++++++++++++
1 file changed, 141 insertions(+)
create mode 100644 figures/Schmidt2018_dyn/run_network_simulations.py
diff --git a/figures/Schmidt2018_dyn/run_network_simulations.py b/figures/Schmidt2018_dyn/run_network_simulations.py
new file mode 100644
index 0000000..a04938c
--- /dev/null
+++ b/figures/Schmidt2018_dyn/run_network_simulations.py
@@ -0,0 +1,141 @@
+import os
+
+from multiarea_model import MultiAreaModel
+from start_jobs import start_job
+from config import submit_cmd, jobscript_template
+from config import base_path
+
+"""
+This script provides the code to execute all simulations presented in
+Schmidt M, Bakker R, Shen K, Bezgin B, Diesmann M & van Albada SJ
+(2018) A multi-scale layer-resolved spiking network model of
+resting-state dynamics in macaque cortex.
+
+Needs to be simulated with sufficient
+resources, for instance on a compute cluster.
+"""
+
+# Common parameter settings
+input_params = {'rate_ext': 10.}
+neuron_params = {'V0_mean': -150.,
+ 'V0_sd': 50.}
+sim_params = {'num_processes': 20, # Needs to be adapted to the HPC system used
+ 'local_num_threads': 24, # Needs to be adapted to the HPC system used
+ 'recording_dict': {'record_vm': False}}
+
+
+"""
+Simulation with kappa = 1. leading to the low-activity fixed point
+shown in Fig. 2.
+"""
+d = {}
+
+sim_params.update({'t_sim': 10500.})
+conn_params = {'g': -16.,
+ 'fac_nu_ext_TH': 1.2,
+ 'fac_nu_ext_5E': 1.,
+ 'fac_nu_ext_6E': 1.,
+ 'av_indegree_V1': 3950.}
+network_params = {'N_scaling': 1.,
+ 'K_scaling': 1.,
+ 'connection_params': conn_params,
+ 'neuron_params': neuron_params,
+ 'input_params': input_params}
+
+M_LA = MultiAreaModel(network_params, simulation=True,
+ sim_spec=sim_params)
+
+# start_job(M_LA.simulation.label, submit_cmd, jobscript_template)
+
+
+"""
+Simulation with kappa = 1.125 leading to the high-activity fixed point
+shown in Fig. 2.
+"""
+sim_params.update({'t_sim': 10500.})
+conn_params = {'g': -16.,
+ 'fac_nu_ext_TH': 1.2,
+ 'fac_nu_ext_5E': 1.125,
+ 'fac_nu_ext_6E': 1.41666667,
+ 'av_indegree_V1': 3950.}
+network_params = {'N_scaling': 1.,
+ 'K_scaling': 1.,
+ 'connection_params': conn_params,
+ 'neuron_params': neuron_params}
+
+M_HA = MultiAreaModel(network_params, simulation=True,
+ sim_spec=sim_params)
+p, r_HA = M_HA.theory.integrate_siegert()
+# start_job(M_HA.simulation.label, submit_cmd, jobscript_template)
+
+
+"""
+Simulation with kappa = 1.125, chi=1
+Presented in Fig. 2, 4, and 8.
+"""
+sim_params.update({'t_sim': 10500.})
+conn_params = {'g': -11.,
+ 'fac_nu_ext_TH': 1.2,
+ 'fac_nu_ext_5E': 1.125,
+ 'fac_nu_ext_6E': 1.41666667,
+ 'av_indegree_V1': 3950.,
+ 'K_stable': '../SchueckerSchmidt2018/K_prime_original.npy'}
+network_params = {'N_scaling': 1.,
+ 'K_scaling': 1.,
+ 'connection_params': conn_params,
+ 'neuron_params': neuron_params}
+
+M_stab = MultiAreaModel(network_params, simulation=True,
+ sim_spec=sim_params)
+p, r_stab = M_stab.theory.integrate_siegert()
+# start_job(M_stab.simulation.label, submit_cmd, jobscript_template)
+
+
+"""
+Simulation with kappa = 1.125, chi=1.9
+Presented in Fig. 4 and all following.
+"""
+sim_params.update({'t_sim': 100500.})
+conn_params = {'g': -11.,
+ 'fac_nu_ext_TH': 1.2,
+ 'fac_nu_ext_5E': 1.125,
+ 'fac_nu_ext_6E': 1.41666667,
+ 'av_indegree_V1': 3950.,
+ 'K_stable': '../SchueckerSchmidt2018/K_prime_original.npy',
+ 'cc_weights_factor': 1.9,
+ 'cc_weights_I_factor': 2.}
+network_params = {'N_scaling': 1.,
+ 'K_scaling': 1.,
+ 'connection_params': conn_params,
+ 'neuron_params': neuron_params}
+
+M_stab = MultiAreaModel(network_params, simulation=True,
+ sim_spec=sim_params)
+p, r_stab = M_stab.theory.integrate_siegert()
+# start_job(M_stab.simulation.label, submit_cmd, jobscript_template)
+
+
+"""
+Simulations with kappa = 1.125
+and varying chi, presented in Fig. 4 and 8.
+"""
+for cc_weights_factor in [1.4, 1.5, 1.6, 1.7, 1.75, 1.8, 2., 2.1, 2.5]:
+ sim_params.update({'t_sim': 10500.})
+ conn_params = {'g': -11.,
+ 'fac_nu_ext_TH': 1.2,
+ 'fac_nu_ext_5E': 1.125,
+ 'fac_nu_ext_6E': 1.41666667,
+ 'av_indegree_V1': 3950.,
+ 'K_stable': '../SchueckerSchmidt2018/K_prime_original.npy',
+ 'cc_weights_factor': cc_weights_factor,
+ 'cc_weights_I_factor': 2.}
+
+ network_params = {'N_scaling': 1.,
+ 'K_scaling': 1.,
+ 'connection_params': conn_params,
+ 'neuron_params': neuron_params}
+
+ M_stab = MultiAreaModel(network_params, simulation=True,
+ sim_spec=sim_params)
+ p, r_stab = M_stab.theory.integrate_siegert()
+ # start_job(M_stab.simulation.label, submit_cmd, jobscript_template)
--
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