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Learning Spiking Neural Networks

This readme file purpose is a recopilation of concepts, links, paper, resources and others as recall/information point.

Papers

Tools

https://www.nest-simulator.org/

Tutorials

Basic concept for Computer guys/gals like me :-)

Creating Environment.

wget https://repo.anaconda.com/archive/Anaconda3-2019.10-Linux-x86_64.sh
bash ./Anaconda3-2019.10-Linux-x86_64.sh

git clone https://github.com/juanmav/spiking.git
cd spiking
apt-get install libgl1-mesa-glx libegl1-mesa libxrandr2 libxrandr2 libxss1 libxcursor1 libxcomposite1 libasound2 libxi6 libxtst6 libopenblas-dev
conda create -n spiking python=3.6
conda install -c conda-forge ffmpeg pypng nest-simulator=*=mpi_openmpi* jupyterlab matplotlib pillow python-dotenv mpi4py
conda install -c conda-forge scikit-image
conda install -c conda-forge libopencv opencv py-opencv
# for local development install nest without openmpi
conda install -c conda-forge nest-simulator mpi4py
python testPlot.py

conda install -c conda-forge python-dotenv

The last command should create two images (test0.png and test1.png) if it does the installation was successful.

Some stuff, how things are "connected"

how connections are

To run the main simulation

python main.py

You can check results on the ./output folder.

Output folder layout

Simplified

TODO

  • Improve LayerRecorder
  • Move functions from main.py to utils and/or another tools.
  • Make parameters logs for each run. (connections, frequencies, array size, etc etc).
  • Document ./output folder layout.

https://en.wikipedia.org/wiki/Cortical_spreading_depression

https://www.frontiersin.org/articles/10.3389/fnbeh.2019.00165/full

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My notebook to learn Nest Simulator API

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