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INM-6 / multi-area-model

A large-scale spiking model of the vision-related areas of macaque cortex.
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Two sets of parameters for initializing membrane potential #55

Open heplesser opened 9 months ago

heplesser commented 9 months ago

The default parameters file defines parameters for initializing the membrane potential of neurons in two places. First we have

https://github.com/INM-6/multi-area-model/blob/7110623fd1b6d5d2aaf1ea195e974c8462aca4fd/multiarea_model/default_params.py#L78-L86

and then

https://github.com/INM-6/multi-area-model/blob/7110623fd1b6d5d2aaf1ea195e974c8462aca4fd/multiarea_model/default_params.py#L107-L115

The comments in both places are very similar and it is not clear to me which of the two sets of parameters are actually used (from https://github.com/INM-6/multi-area-model/blob/7110623fd1b6d5d2aaf1ea195e974c8462aca4fd/multiarea_model/simulation.py#L468 it seems the second one; the first seems entirely unused).

I find the second set of values rather unphysiological with a mean well below typical GABA reversal potential (-90 mV if I am not wrong), and with one std deviation stretching to -150 mV.

With a spike threshold of -50 mV (https://github.com/INM-6/multi-area-model/blob/7110623fd1b6d5d2aaf1ea195e974c8462aca4fd/multiarea_model/default_params.py#L93), for the first set of parameters (-58±10 mV) about 21% of all neurons will be initialized to superthreshold membrane potentials, for the second set (-100±50 mV) about 16%. These neurons will all spike simultaneously in the first time step. How sensible is this?

At least for benchmarking, a massive barrage of spikes in a single time step can lead to some problematic (because atypical) resizing of data structures. Since the membrane potential distribution must be zero at the threshold, would it not make more sense to initialize the membrane potential with a lognormal distributions stretching from V_th down towards -inf?