Neural network simulator developed by Felix Hoffmann for his PhD. Original at https://github.com/synsrv/src_net.

Network simulation using Brian 2 and Pypet written to analyse the survivability of transient synapses of cortical neurons.

To run the network simulation a Python 3 environment with Brian 2 (with patches), and Pypet is required. Git also has to be installed. Detailed dependencies are listed in environment.yml. Below is an example installation routine for setting up a conda environment. This assumes that you already have anaconda or miniconda installed.

#!/bin/sh

conda env create -f environment.yml
conda activate excinhbal

This will also install Brian2 with patches.

Brian2 patches are required for long simulations. We maintain our own repository of Brian2 with patches applied: https://github.com/excinhbal/brian2/branches

In order to upgrade Brian2 to an up-to-date version:

1. clone our Brian2 repository
2. git remote add upstream https://github.com/brian-team/brian2.git
3. git fetch upstream
4. git checkout origin/<our most up to date branch> -b <new release tag>__excinhbal_fixes
5. git rebase <new release tag>
6. fix conflicts
7. git log should now show a few commits like this https://github.com/excinhbal/brian2/commit/b3c7d3adadabb7d4f0b4b70dca818787a7714900 as newest commits of the branch and the next oldest commit should be the Brian2 release commit of the version that you wanted to upgrade to
8. push the new branch to origin (our Brian2 repository)
9. edit this repository’s requirements.txt to point to the new branch

For details about the patches check out #1057.

Get the code from this repository including submodules with

git clone  --recurse-submodules https://github.com/excinhbal/network

It is highly recommended to limit the level of parallelization when building the standalone_cpp simulator. In $HOME/.brian/user_preferences write, where 4 is the number of CPU cores your PC has:

[devices.cpp_standalone]
extra_make_args_unix = ["-j4"]

To verify your installation, within src_net run

./run_test.sh -l tests/net_tests/test_standard_net/

This will create a directory tests/ on the same level as src_net where the code is copied an executed.

To run simulations exploring different parameter sets, create an explored_params.py in src_net/net/, as for example found in any of the tests in net_tests/. In the input_dict of explored_params.py specify the parameter setting of your choice and the runn simulation via

./run.sh -l -n 2 -P "_two-concurrent-sims" -E

This will create running/ and completed/ directories on the same level as src_net/. Once finished, the simulation directory is moved from running/ to completed/.

There are multiple sets of tests currently, they fall in two broad categories:

1. tests that can be run with pytest: pytest tests/pytests
2. all other tests, which can be run using ./run_tests.sh as shown above