PyNNA free Python package for simulator-independent specification of neuronal network models | |
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PyNN Ranking & Summary
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- License:
- Freeware
- Price:
- FREE
- Publisher Name:
- The NeuralEnsemble Community
- Publisher web site:
- http://neuralensemble.org/
- Operating Systems:
- Mac OS X
- File Size:
- 207 KB
PyNN Tags
PyNN Description
A free Python package for simulator-independent specification of neuronal network models In other words, you can write the code for a model once, using the PyNN API, and then run it without modification on any simulator that PyNN supports (currently NEURON, NEST and PCSIM).The API has two parts, a low-level, procedural API, similar to that in PyNEST (functions create(), connect(), set(), record(), record_v()), and a high-level, object-oriented API (classes Population and Projection, which have methods like set(), record(), setWeights(), etc.).The low-level API is good for small networks, and perhaps gives more flexibility. The high-level API is good for hiding the details and the book-keeping, and is intended eventually to have a one-to-one mapping with NeuroML.The other thing that is required to write a model once and run it on multiple simulators is standard cell models. PyNN translates standard cell-model names and parameter names into simulator-specific names, e.g. standard model IF_curr_alpha is iaf_neuron in NEST and StandardIF in NEURON, while SpikeSourcePoisson is a poisson_generator in NEST and a NetStim in NEURON. Only a few cell models have been implemented so far.NOTE: PyNN is licensed and provided under the terms of the CeCILL licence.
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