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Thanks very much for your help. As you suggested, I installed the latest version of NEURON (7.7.0). I also corrected the two issues you identified in the code: from neuron import h h.load_file("stdrun.hoc") pc = h.ParallelContext() pc.gid_clear() section = h.Section() pc.set_gid2node(0, pc...

I would like to use BBSaveState to take a snapshot of the state of my parallel simulation, for use as starting conditions for further model runs. However, when I call BBSaveState.save_test(), a segmentation fault occurs: Segmentation fault: 11 My simulation is quite complicated. However, even the fo...

I have found some more curious results in a gap junction connected network using the linearmechanism class. The following link shows the results of running a network of 75 identical cells connected by gap junctions implemented by linearmechanism. Initial conditions were set by voltage clamping each ...

Thanks again for your help. I have implemented the gap junction using linearmechanism, which I understand should be equivalent to using the Linear Circuit Builder. With just two cells, I am unable to generate any unstable or chaotic behaviour. Even if the cells start unsynchronised, they very quickl...

Hi Ted, Thanks for you reply. This makes a lot of sense. I developed the example in order to isolate an issue I was having with my full model, which consists of many thousands of gap junction-coupled cells. In the model each cell is identical, and receives the same stimulating current. At first, the...

Hi, I am trying to resolve an issue using NEURON model gap junctions, in which spurious voltage changes occur in gap junction-connected sections. The following Python code demonstrates the issue. There are three identical sections, each receiving an identical depolarizing current. The first two sect...