PyNEST implementation

Installing the python package microcircuit

The PyNEST implementation of the model is provided in the form of a python package microcircuit.

We recommend installing the python package inside a python environment:

• Create a python environment

  python -m venv venv
  

• Activate the python environment:

  source venv/bin/activate
  

• Update pip:

  pip install -U pip
  

The microcircuit python package can be installed by one of the following methods:

1. Install the package directly from PyPI:

   pip install microcircuit
   

   Optionally, you may want to install additional dependencies by using extra flags:

   Option	Flag
   runtime testing	test
   development tools	dev
   documentation build tools	doc

   Example:

   pip install microcircuit[dev,doc] 
   

2. Clone the repository and install the python package from the local sources:

    git clone https://github.com/inm-6/microcircuit-PD14-model
    pip install microcircuit-PD14-model/PyNEST
   

3. Install the package from the repository without cloning the entire repository:

   pip install "git+https://github.com/INM-6/microcircuit-PD14-model.git/#egg=microcircuit&subdirectory=PyNEST"
   

Software requirements

• NEST (see NEST installation)

  We recommend installing NEST locally within the virtual environment:

  git clone https://github.com/nest/nest-simulator
  ## for a specific <VERSION> (e.g. <VERSION>=v3.9), use
  ## git clone --depth 1 --branch <VERSION> https://github.com/nest/nest-simulator
  cd nest-simulator
  mkdir build
  cd build
  pip install -r ../requirements_pynest.txt
  cmake ..
  make
  make install
  

• Python 3.x

• docopt-ng, matplotlib, numpy, psutil, ruamel.yaml, scipy (handled by python package dependencies)

Testing

To enable testing, make sure that the microcircuit package is installed with testing dependencies:

pip install microcircuit[test]

Executing

pytest

in the root directory of the repository microcircuit-PD14-model runs the test(s) in microcircuit-PD14-model/PyNEST/tests.

Usage

After installation, the microcircuit python package can be imported in a python application using

import microcircuit

See this example for a more detailed illustrations of how the package can be used.

Memory requirements

Performance benchmarking

Recent performance benchmarking results for the microcircuit model can be found here.

Implementation details

This implementation uses the iaf_psc_exp neuron and the static_synapse synapse models provided in [NEST]. The network is connected according to the fixed_total_number connection rule in NEST. The neuron dynamics is integrated in a time-driven manner using exact integration with a simulation step size sim_resolution (Rotter & Diesmann, 1999).

The PyNEST implementation runs with NEST 3.9 (Terhorst et al., 2025).

Simulation parameters (defaults)

References

Rotter & Diesmann (1999), Exact digital simulation of time-invariant linear systems with applications to neuronal modeling. Biological Cybernetics 81(5-6):381-402. doi:10.1007/s004220050570

Terhorst et al. (2025). NEST 3.9. Zenodo. doi:10.5281/zenodo.17036827

License

This project is licensed under GNU General Public License v2.0 or later. For details, see here.