5 Jun
2023
5 Jun
'23
2:13 p.m.
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.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:
> > Hi everyone, has anyone successfully added a gap junction to an
> > existing model using NESTML? I would like to add gap junction support
> > to the aeif_cond_alpha neuron model but it is unclear how this can be
> > done within NESTML. As suggested by Charl, I started to look into
> > updating the jinja templates but I am not sure this will be possible
> > since both the input/output of the neuron and the model's equation must
> > be updated to support gap junctions. If anyone has any suggestions or
> > if anyone has NESTML code for adding a gap junction to an existing
> > model, I would be very appreciative. Thanks!
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