3 Feb
2021
3 Feb
'21
6:02 p.m.
Dear Charl,
just a quick update on this triplets issue. First of all, thank you so much
again for taking the time and helping me with this!
I noticed from your code I wasn't setting all time constants and delays for
the triplets in both neuron and synapse model correctly, and that solved
most of the problem. I still noticed some small differences to NEST
calculated weights, though, when delays were small and simulation was a bit
longer (delay=1.5ms and sim_time=100000ms for example).
I looked a bit more into it, and I think the problem was that on NEST, in
practice, all traces are used before increment:
1) Potentiation due to a postsynaptic spike is executed before the update
on presynaptic trace (Kplus_ or r1). Which means that, if there was a
presynaptic spike exactly at post spike + delay, the value of r1 used is
the value propagated since the last presynaptic spike, but before the
increment.
2) Depression due to presynaptic spike uses get_K_value(), which gets the
K_value (o1) from the postsynaptic neuron. I don't know exactly in which
order things are executed, but I guess the value of the synaptic weight is
updated before K_value on the neuron model. Or at least assuming that is
how it works seems to solve the problem.
In summary, the problem seems to be fixed:
1) In your code: by including before_increment=True for all traces (r1,o2
and o1,r2).
2) In my code: by subtracting 1 from o1_at_pre_spk when there is a
postsynaptic spike exactly at pre spike - delay. There is no need to
subtract anything from r1 in my case, since I execute depression after
potentiation as in NEST code. So in practice, r1 is used before increment.
The differences are small, but the weights seem to match better now.
Cheers,
Júlia
Em seg., 11 de jan. de 2021 às 20:17, Julia Gallinaro <juliavg(a)gmail.com>
escreveu:
Dear Charl,
That is great. I have run some tests here, and am also convinced by this
result. Thank you so much for putting effort into this!
All the best for the new year too!
cheers,
Júlia
Em dom., 10 de jan. de 2021 às 08:32, Charl Linssen <
nest-users(a)turingbirds.com> escreveu:
Dear Júlia,
Best wishes for the new year! I have tinkered around a bit with the
script, and rewrote it along these lines:
- time is evolved strictly chronologically from spike to spike
- there is a helper function (with parameter t) to obtain the pre or post
trace value at any time t
- dendritic delay is accounted for by simply adding the delay value to
all the postsynaptic somatic spike times, to obtain the postsynaptic
synaptic-perspective spike times
With these changes, the NEST weight evolution seems to be replaced
precisely—please see the bottom panel in the figure generated by the
script. Caveat: I only did a visual comparison for very long simulation
time, it would be great if you could confirm that you are indeed also
convinced by this result!
Cheers,
Charl
On Wed, Dec 16, 2020, at 11:32, Julia Gallinaro wrote:
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:
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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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