Hi Charl,
Thanks a lot for looking into this and for the suggestions. I will do
some more tests considering what you wrote and let you know if I have
any updates.
I wish you nice Holidays!
Best,
Júlia
On Wed, 16 Dec 2020 10:22:22 +0100
"Charl Linssen" <nest-users(a)turingbirds.com> wrote:
Hi Júlia,
Thanks for writing in. Of course, we try to ensure the correctness of
NEST Simulator by validation and unit testing, but it is a complex
piece of software with a long history, and it is not impossible that a
bug may exist in the triplet STDP synapse. I am not the original
author of that model, but I've been working with other synaptic
plasticity models and would be happy to investigate.
You probably know already that the (dendritic) communication delay
introduces a few quirks in the code. In particular, the postsynaptic
spike arrives at the synapse delayed by this amount, whereas the
postsynaptic trace values are obtained without the delay (that is, at
the actual time that the somatic action potential is fired).
I had a look at your script, and couldn't immediately find anything
out of the ordinary. You reproduced the NEST buffering methodology
quite accurately (postsynaptic spikes are buffered, and only handled
after a presynaptic spike arrives), but during this stage of finding
the reason for the discrepancy, it might help to just treat all the
spikes (pre and post) chronologically.
Perhaps you already found this, but there are some unit tests in place
in pynest/nest/tests/test_stdp_triplet_synapse.py, that do some
behavioural validation of the synapse. I don't think these cover the
general case (as in your script), but might help honing in on a bug.
I'll try to get back to you over the next few weeks (modulo the
holidays...) with more details. If there are any updates from your
side in the mean time, please do share!
Best regards,
Charl Linssen
On Thu, Dec 10, 2020, at 19:16, Julia Gallinaro wrote:
Dear NEST community,
I am working with the triplets STDP connection on NEST simulations,
and I am
interested in how the weight dynamics change when the spike
trains are altered in some specific ways.
In order to do that, I run a network simulation using NEST and the
triplets STDP
rule and save the full spike trains of two neurons which
are synaptically connected (one pre and one post). I then recreate the
weight changes on a code outside the NEST loop, so that I can
manipulate the spike trains and observe what happens to the synaptic
weights.
Trying to validate this approach, though, I find that my code
(outside NEST loop)
generates different weight values than the NEST
simulation when using the same spike trains generated during the
simulation. I guess I have some error in my implementation of the
triplets rule. I thought it could be something with the implementation
of the delays, or the moment when the weights are measured in the
simulation, but I have had no success trying to fix it yet.
I know this is not exactly a NEST issue, but I thought I would give
it a try and
ask here at the list. In case someone has already worked
with the triplets rule and could point me out to what is/could be
wrong in my implementation, I would very much appreciate it :)
>
> Thanks!
>
> best,
> Júlia
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>
> *Attachments:*
> * triplets_NEST_offline.py
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