On Mon, May 11, 2020 10:05:00 +0200, Julia Gallinaro wrote:
thank you for your reply! I am not familiar with NESTML yet, but I
go through the documentation you sent and try to implement a model as
you suggested. Using exponential PSC would not be a problem for me.
I had meanwhile found a workaround, though. When setting the parameters
for the vogels_sprekeler_synapse, I set both 'Wmax' and the parameter
'weight' to a negative value:
It now works, and seems to give me the results as expected. Would you
know if this is equivalent to using the rule with positive weights and
multiplying it by -1 afterwards?
The sign of the weight is not changed by the depression/facilitation
functions. They only modify the magnitude and then copy the sign back on
to the value. So, using negative values for weight and Wmax is the
correct thing to do here.
This is the C++ implementation for your reference:
We check to ensure that Wmax and the initial weight are of the same
sign, so that an inhibitory synapses cannot be flipped to an excitatory
I *think* a negative weight is "standard convention" for inhibitory
synapses in NEST, but I cannot find a reference to this at the moment.
Ankur Sinha (He / Him / His) | https://ankursinha.in
PhD candidate in computational neuroscience at UH Biocomputation |
Research Fellow at the Silver Lab | http://silverlab.org/
Free/Open source community volunteer at the Fedora project |
Time zone: Europe/London