Generalized integrate-and-fire model#427
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November 4, 2016 11:35
…for `pyNN.neuron`, using NMODL description from Christian Roessert
… rather than 0 mV, during the refractory period (to match the behaviour of other IF models).
…, so it is not necessary to use the MyModule approach. Also modified the NEURON implementation to increment the eta and gamma variables at spike onset rather than after the refractory period. This matches the description in Pozzorini et al., and the behaviour of the NEST implementation.
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FYI: GLIF models from the Allen Institute Cell Types Database project have been converted to LEMS (for eventual incorporation into NeuroML2) here: https://github.com/OpenSourceBrain/AllenInstituteNeuroML/tree/master/CellTypesDatabase/models/GLIF |
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@croessert does this look ok to you? |
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@pgleeson Thanks for the info |
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In the absence of further comments, merging this now. |
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for NEST and NEURON backends. Brian implementation still needed.
Requires development version of NEST (Github master branch).
Only simple, cond-exp synapses for now.