Dear Atiyeh,

Thanks for the clarifications. It looks like the S() function is only used to make sure that positive weights stay positive, and negative weights stay negative, i.e. the weights never change sign. Am I right to assume that you are not using any synaptic plasticity rules in your network (i.e. you only use the static_synapse)?

You could ensure that this condition holds by construction of your network. For example, if you make a connection to this neuron with a positive w_ji, then S(w_ji) is nonzero but S(-w_ji) is zero, so there is an excitatory postsynaptic response but no inhibitory postsynaptic response. If you make a connection to this neuron with a negative w_ji, then the opposite holds, so you get only the inhibitory contribution and not the excitatory one. So S() might be better implemented outside of the NESTML model; you can ensure the same result during network construction, when you are making calls to nest.Connect().

For your second question, yes, that sounds correct. For your third question, do you mean for the simulation to run faster? Are you already running multi-threaded? See e.g. setting nest.local_num_threads to a value larger than one; detailed documentation for running NEST using multiprocessing can be found at https://nest-simulator.readthedocs.io/en/latest/hpc/parallel_computing.html.

I hope this helps, please let us know how you fare!

With kind regards,
Charl


On Mon, Nov 27, 2023, at 16:06, atiye nejadebrahim wrote:
Dear Charl, 
thanks for your reply, 
in these equations 
Inline image
 the function S{x} = x, if x ≥ 0, and 0 if x < 0.

in the neuron model, I have the  only first term without s{w}, 
1. my question is how can I add s{w} in the neuron model? 
2.for the second term, I defined spike generators and parrot neurons and connect parrot neurons by static synapses to my desired neuron populations. can I consider synaptic weight  of parrent neurons' conncetions to neuron poulations as s{w} for second term?
3. How can I decrease the time of simulation? 
Best, 
Atiyeh 


On Tuesday, November 21, 2023 at 06:17:20 PM GMT+1, Charl Linssen <nest-users@turingbirds.com> wrote:


Hi Atiyeh,

Let me try to understand fully the model that you wish to implement. I am not sure what the "S{...}" is, is it a generic function? Could you specify in case there is a specific S() that you would like to use in your model?

Cheers!
Charl


On Tue, Nov 21, 2023, at 09:42, atiye nejadebrahim wrote:
Dear All, 
I am going to add weights for excitatory and inhibitory synaptic currents according to this equation:

Inline image
can you help me how I can add S(Wji) to a simple neuron model like one I attached to this email?
Thanks and BR, 
Atiyeh 

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