Connection-set algebra (CSA) is a novel and general formalism for the description of connectivity in both small-scale and large-scale neuronal network models. It provides operators to form more complex sets of connections from simpler ones and also provides parameterization of such sets. CSA can be used as a component of neuronal network simulators or other tools. A Python implementation is available on GitHub.
CSA was developed within the INCF Program on Multiscale Modelling
CSA description paper: Mikael Djurfeldt (2012) "The Connection-set Algebra---A Novel Formalism for the Representation of Connectivity Structure in Neuronal Network Models" Neuroinformatics 10(3), 1539-2791,http://dx.doi.org/10.1007/s12021-012-9146-1
Supported in PyNN, NEST, NineML (experimental branch). Supports Python 3, TravisCA, Coveralls
Requirements: Numpy, Matplotlib
License: GNU General Public License