This repository contains code to simulate a spiking neural network model based on the connectome data of the fruit fly. It is based on the original model but is further developed by the Bidaye lab.
For more information on the general structure of this repo, see this template repo.
Details about how to use the model are given in the separate workflow scripts:
| file | content |
|---|---|
| example.ipynb | General usage |
| graph_for_cytoscape.ipynb | Visualizations for cytoscape |
| heatmap_2freq.ipynb | Custom 2D frequency comparison |
# get source code
git clone https://github.com/nspiller/spiking_neural_network_model
cd spiking_neural_network_model
# create conda environment with necessary dependencies
conda env create -n spiking_neural_network_model -f environment.yml
conda activate spiking_neural_network_model
# install project code as local local python module
pip install -e .
To significantly speed up the simulations, install the the following through the Individual components tab in the Visual Studio Installer:
MSVC v143 VS2022 C++ x64/x86 built tools(or latest version)Windows 10 SDK(latest version)
See official Brian2 documentation on "Requirements for C++ code generation" for more details.
# pull from github
cd spiking_neural_network_model
git pull origin main