I have been contributing to BMTK (https://github.com/alleninstitute/bmtk), which uses NEURON to model biophysical neural networks. I talked briefly with Ted at SfN about this issue I've been having implementing gap junctions so thought I would formalize that here to see if anyone can help.
BMTK has two independent steps to creating a model; building and simulation. Building the model actually doesn't use NEURON at all, it simply creates h5 files that store information about the cells, connectivity, etc. The simulation step loads these files and creates a NEURON model out of them.
I have provided a minimal working example of a synaptic connection (chemical synapse) between two cells here:
https://github.com/latimerb/BLA_SingleC ... apJunction
The readme file in the top level of the repository explains how to run the BMTK simulation.
Digging through the BMTK code is a bit of a chore, but we managed to identify the place where synapses are made:
https://github.com/latimerb/bmtk/blob/d ... ll.py#L161
Our thought was to simply handle the gap junction here through point processes as we have seen done in the past:
https://github.com/latimerb/BLA_SingleC ... on/test.py
However, when we tried that, we got the message "segmentation fault (core dumped)" when h.run() was called from BMTK. This is where the simulation gets initialized and run:
https://github.com/latimerb/bmtk/blob/d ... or.py#L228
I noticed that pc.psolve() is not used in BMTK, could that be a problem? Is there anything to do with how the simulation is initialized and run that would conflict with the gap junction method outlined above? Any guidance is greatly appreciated.
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