2 Oct
2023
2 Oct
'23
11:27 a.m.
Hi Anthony,
Thank you for writing in. This phenomenon is probably the result of an internal
optimization that NEST carries out: the synaptic weight is only ever actually updated when
a synapse receives a presynaptic spike. At that time, the updated weight is needed so that
the postsynaptic potential has the right amplitude. However, postsynaptic spikes are
buffered and not immediately processed into a weight update, because the updated weight is
not yet needed at the time of the post spike (there is no synaptic transmission occurring
in that case).
To amend this, try to insert a "dummy" presynaptic spike at the very end of your
simulation. It should be far away from other spikes to as to not change the weight too
much, but it will trigger the weight update due to the previous (buffered) postsynaptic
spike.
Please see the NESTML STDP windows tutorial
(https://nestml.readthedocs.io/en/latest/tutorials/stdp_windows/stdp_windows…) for a
full example.
Hope this helps!
All the best,
Charl
On Mon, Oct 2, 2023, at 00:23, Tony Lee wrote:
Hi,
I'm attempting to recreate the STDP dynamic figure like that of [this
figure](https://www.jneurosci.org/content/jneuro/20/23/8812/F1.large.jpg?wi…
(from [this paper](https://www.jneurosci.org/content/20/23/8812)).
However, no matter how I tune the time-constants and transmission
delays, it seems that the potentiation side of the dynamics is just
missing.
I've checked the NEST ML equations and C++ header files and they look
fine.
Thus, I am needing a second opinion to see if I am missing something
obvious.
[Here](https://gist.github.com/aoot/9409b939e891a1c823cc7defe97ab479)
is the code in ipynb form and the figure I have (missing the LTP side).
Thank you,
Anthony
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