This repository contains code for the manuscript "Learning function from structure in neuromorphic networks" by Laura Suarez, Blake Richards, Guillaume Lajoie & Bratislav Misic.
We investigated the link between macroscale connectivity and the computational properties that emerge from network dynamics in the human connectome.
We've tried to document the various aspects of this repository with this README file, so feel free to check things out!
This repository can be referenced using
First, you'll need to make sure you have installed the appropriate software packages, and have downloaded the appropriate data files.
- Git clone the suarez_neuromorphicnetworks repository.
- Download the "data" and "raw_results" folder from
and place them into the repository's root directory.
- In the command line, type:
cd suarez_neuromorphicnetworks
conda env create -f environment.yml
conda activate rc- Git clone reservoir repository.
- And install it in the newly created environment:
cd reservoir
pip install .- Then, follow these steps sequentially (i.e., first "Run simulations", then "Compile results" and then "Analyses and Figures").
python scripts/01_rc_workflow/1_run_rc_workflow.py
python scripts/01_rc_workflow/2_get_network_properties.pypython scripts/02_fetch_results/fetch_task_results.py
python scripts/02_fetch_results/fetch_net_props_results.pypython scripts/03_analysis/figX.py(replace X by the number of the figure)
- Git clone the suarez_neuromorphicnetworks repository.
- Download the "data" and "proc_results" folders from
To run the analysis presented in Figure "X" of the manuscript, you just need to run:
python scripts/03_analysis/figX.pyOpen an issue on this repository and someone will try and get back to you as soon as possible!