Developed by the Department of Brain and Behavioral Sciences at the University of Pavia, the BSB is a component framework for neural modelling, which focusses on component declarations to piece together a model. The component declarations can be made in any supported configuration language, or using the library functions in Python. It offers parallel reconstruction and simulation of any network topology, placement and/or connectivity strategy.

The BSB requires Python 3.8+.

This software can be installed as a Python package from PyPI through pip:

pip install "bsb>=4.0.0a0"

Developers best use pip's editable install. This creates a live link between the installed package and the local git repository:

 git clone [email protected]:dbbs-lab/bsb
 cd bsb
 pip install -e .[dev]
 pre-commit install

The scaffold framework is best used in a project context. Create a working directory for each of your modelling projects and use the command line to configure, reconstruct or simulate your models.

You can create a quickstart project using:

bsb new my_model --quickstart
cd my_model

You can use your project to create reconstructions of your model, generating cell positions and connections:

bsb compile -p

This creates a network file and plots the network.

The default project currently contains no simulation config.

All contributions are very much welcome. Take a look at the contribution guide

Shouldn't be much work, famous last words.