A package for simulator-independent specification of neuronal network models
Description
PyNN (pronounced 'pine') is a simulator-independent language for building
neuronal network models.
In other words, you can write the code for a model once, using the PyNN API and
the Python programming language, and then run it without modification on any
simulator that PyNN supports (currently NEURON, NEST and Brian) and on a number
of neuromorphic hardware systems.
The PyNN API aims to support modelling at a high-level of abstraction
(populations of neurons, layers, columns and the connections between them)
while still allowing access to the details of individual neurons and synapses
when required. PyNN provides a library of standard neuron, synapse and synaptic
plasticity models, which have been verified to work the same on the different
supported simulators. PyNN also provides a set of commonly-used connectivity
algorithms (e.g. all-to-all, random, distance-dependent, small-world) but makes
it easy to provide your own connectivity in a simulator-independent way.
Even if you don’t wish to run simulations on multiple simulators, you may
benefit from writing your simulation code using PyNN’s powerful, high-level
interface. In this case, you can use any neuron or synapse model supported by
your simulator, and are not restricted to the standard models.
Documentation: http://neuralensemble.org/docs/PyNN/
Mailing list: https://groups.google.com/forum/?fromgroups#!forum/neuralensemble
This package supports the NEURON, NEST, and Brian simulators.
