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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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Add Jupyter Notebook for EBRAINS with down-scaled MAM #33

Closed jhnnsnk closed 1 year ago

jhnnsnk commented 2 years ago

The notebook illustrates the simulation workflow with a down-scaled version of the multi-area model. It is based on a draft by @terhorstd. I have added the functionality to write a custom config.py from within the notebook such that no additional files are necessary. Besides, I have computed the instantaneous firing rates from the spike data and plotted them. Please check if the calculation is correct. Currently the mean-field prediction gives about 30 spikes / s and the simulation about 17 spikes / s and I am not sure if this discrepancy is expected. I have also added some documentation on running the notebook in the Jupyter Lab on EBRAINS.

On EBRAINS the SLN fit failed due to an IndexError, but locally on my laptop it worked; so I assume that it is an issue with some Python package version. I have added the IndexError to the exception such that if it occurs the hard-coded fit parameters are used in the same way as when R is not available for calculation.

jarsi commented 1 year ago

Thanks for adding this new feature, I'll go ahead and merge.