[NEST Users] Re: Adding gap junctions using NESTML

Hi Beck, Happy to hear that the gap junctions are working (mostly) in order! Please apologize my late reply, I came down with a nasty bug for a while. The trick here (hopefully) is to grab a different SynapseCollection, namely one that includes only the gap junctions and not the normal synapses (static_synapse). You can pass the "synapse_model" key to the GetConnections() call, which selects only the synapses by that name, for instance: gap_syn = nest.GetConnections(pre_neuron, post_neuron, synapse_model="gap_junction") I've added a new test for this in: https://github.com/nest/nestml/pull/907/commits/cd24e9c8a16e908f73f26e03519… Please let me know if this is what you're looking for. With kind regards, Charl On Tue, May 30, 2023, at 23:04, Beck Strohmer wrote: Hi all, I am trying to update the weight of the gap junctions implemented via NESTML in between runs of a split simulation. However, when I update the weight using "nest.SetStatus(synapse_collection,{'weight':some_weight})", I can see that the static synapse weights between the populations are also updated instead of only the gap junction weights. Is there a way to correct this so that only gap junction weights are updated? Thanks for any help! Best, Beck On Wed, May 24, 2023 at 4:03 PM Beck Strohmer <bstrohmer(a)gmail.com> wrote: Thanks Charl! I successfully added the gap junction to the aeif_cond_alpha neuron model using NESTML. A very rudimentary quantitative test shows that without the gap junction, there is a mean Vm difference over the plot of 0.223mV and with a gap junction, this is reduced to 0.043mV. You can see that there is an initial difference in Vm due to the neurons being initialized with different values, they converge quickly due to the gap connection.[image: gap_test_nestml.png] On Tue, May 16, 2023 at 5:41 PM Charl Linssen <nest-users(a)turingbirds.com> wrote: Hi all, We now have a prototype for support of gap junctions via NESTML. The code is being tested right now on the "iaf_psc_exp" (linear dynamics) and "aeif_cond_exp" (nonlinear dynamics) neuron models and can be found at https://github.com/nest/nestml/pull/907 The pull request is still in a draft stage; some documentation still needs to be added, but most of all I would like to have more strict numerical validation of the results. If anyone could recommend some simple systems (for instance, involving only two neurons connected by one gap junction), in particular those that have a closed-form algebraic solution of the dynamics, or those that converge to a known solution under a set of representative conditions, this would be much appreciated. Please let me know if you run into any trouble running the prototype! With kind regards, Charl On Tue, Mar 14, 2023, at 11:10, bstrohmer(a)gmail.com wrote: _______________________________________________ NEST Users mailing list -- users(a)nest-simulator.org To unsubscribe send an email to users-leave(a)nest-simulator.org _______________________________________________ NEST Users mailing list -- users(a)nest-simulator.org To unsubscribe send an email to users-leave(a)nest-simulator.org _______________________________________________ NEST Users mailing list -- users(a)nest-simulator.org To unsubscribe send an email to users-leave(a)nest-simulator.org