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vellamike edited this page May 14, 2012 · 8 revisions

Welcome to the libNeuroML Wiki!

Tools relevant for this initiative

Below is a list of tools which are built in, or use Python and which would benefit from a standard library to access, modify and save detailed neuronal morphologies.

Neuronvisio

http://michelemattioni.me/neuronvisio (GitHub: https://github.com/mattions/neuronvisio)

PyNN

http://neuralensemble.org/trac/PyNN

Morphforge

https://github.com/mikehulluk/morphforge

CATMAID

http://www.catmaid.org We reconstruct neuronal circuits (morphology in 3D, synaptic connectivity) as skeletons, surfaces, volumes in CATMAID. We want to be able to export the data into an object model (data format), complement it with ion channel distribution of several types & synaptic mechanisms, and simulate the membrane voltage time series and do virtual current injection etc. on standard simulators. All of this with a easy-to-use, intuitive Python API in a few lines of code.

NEURON

http://www.neuron.yale.edu/neuron

MOOSE

http://moose.sourceforge.net

GENESIS

http://genesis-sim.org/

neuroConstruct

http://www.neuroConstruct.org neuroConstruct generates native simulator code for NEURON, MOOSE and other simulators. It would be a great benefit to be able to generate pure NeuroML descriptions of the model components and run (nearly) identical Python code on these simulators to load the NeuroML and execute the simulations. This scenario is implemented already for a limited number of model types by generating PyNN based scripts which can run on NEURON, Brian and NEST.

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