From 63a2e921f6b348e9d16db838f15276c1a56ce7d4 Mon Sep 17 00:00:00 2001 From: Didi Hou <didi.hou@rwth-aachen.de> Date: Wed, 20 Sep 2023 16:48:01 +0200 Subject: [PATCH] Update VERSION_LOG.md --- VERSION_LOG.md | 36 ++++++++++++++++++++++++++++++------ 1 file changed, 30 insertions(+), 6 deletions(-) diff --git a/VERSION_LOG.md b/VERSION_LOG.md index 2ee11f3..798f5bc 100644 --- a/VERSION_LOG.md +++ b/VERSION_LOG.md @@ -1,25 +1,49 @@ ## MAM v1.1.0 +### New features + +* Improved documentation: added in the README.md file the Try It On EBRAINS button and clear and detailed User instruction for users to be able to follow step-by-step instructions without much background knowledge or experience, delete section Testing on EBRAINS + +* In down-scale multi-area mode, separated all external parameters to Parameters to tun and Default parameters. Parameters to tune consist of 4 parameters we decided to expose to users initially, and default parameters will be tuned by us and are not recommended for users to change + +* Added section Extract and visualize interareal connectivity which plots the area-level relative connectivity as heatmaps. Two heatmaps represent the interareal connectivity of full-scale multi-area model (left) and down-scale multi-area model (right). There are small differences between them although we’re calculating relative connectivity as there’s randomness + +* Added section Simulation Results Visualization. The code is written in separate modules saved as .py files in “./figures/MAM2EBRAINS†to avoid displaying contents that are not relevant to users + +* Added 3 plots in the section Simulation Results Visualization + * 3.1. Instantaneous and mean firing rate across all populations (existed in MAM v1.0.0, refined in MAM v1.1.0) + * 3.2 Resting state plots + * 3.3 Time-averaged population rates + +* The 3.2 Resting state plots figure is plotted based on Fig 5. of the paper 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. PLOS Computational Biology, 14(9): e1006359. https://doi.org/10.1371/journal.pcbi.1006359, yet there are a few differences: + * This plot provides the option for users to choose 3 areas to plot the raster plots instead of fixing V1, V2, and FEF to plot + * The subplot E Correlation coefficient is replaced as Synchrony + * The subplot G only plots the binned spike histograms (gray), not the convolved histograms (black) + ### Enhancements -* The structure of the notebook has been revamped for improved clarity and user navigation. +* Reconstructed the Jupyter Notebook and added Notebook structure as table of contents that enables users to navigate quickly and easily between different sections. (see the notebook structure for details) + +* Added detailed and easy-to-understand descriptions to the 4 exposed parameters and also brief comments for the default parameters -* Enhanced Parameter Descriptions: Parameters are now accompanied by more detailed descriptions, providing users with a clearer understanding and better control over model configurations. +* Added the model overview diagram and a short description of the down-scaled multi-area model at the beginning of the jupyter notebook -* Visualization Enhancements: Dive deeper into your simulation results with the addition of new plots that offer richer insights into the model's behavior. +* Added descriptions of comparable figures in our publications whenever available so that users can compare the down-scaled model with their costumed parameters and the full-scaled model presented in the paper -* Try it on EBRAINS: For users looking for a seamless experience, we've integrated a "Try it on EBRAINS" button. Dive right in and experience MAM on the EBRAINS platform! +* Removed unnecessary print statements in ./multiarea_model/analysis.py and ./multiarea_model/analysis_helpers.py to avoid multiple print that are not relevant to users -* Improved Documentation: The README.de file has been updated with comprehensive user instructions to guide both new and returning users through the features and functionalities of MAM. +* Updated ./.gitignore file to ignore checkpoint files ### Bug fixes * Corrected the separator from "" to "/" in ./multiarea_model/data_multiarea/SLN_logdensities.R to fix the file path of ./multiarea_model/data_multiarea/bbAlt.R + +* Fixed bugs in ./multiarea-model/analysis.py: change np.nan*np.ones(params['t_max'] - params['t_min']) to np.nan*np.ones(int(params['t_max'] - params['t_min'])) ## MAM v1.0.0 ### Bug fixes -* corrected the URL of NEST logo in README.md +* Corrected the URL of NEST logo in README.md -- GitLab