Dear Benedikt,
Yes, this should be possible in NESTML. Define two input ports for b1 and b2 (see the multisynapse example in the documentation for how to do this). The membrane potential (say, V_m) can be used to affect the synaptic currents, e.g.:
I_b1 = f(V_m) * convolve(I_shape, spikes_b1)
I_b2 = g(V_m) * convolve(I_shape, spikes_b2)
for some functions f and g. Then simply enter the membrane potential dynamics as you want it to be, e.g. for multiplicative interaction
V_m' = const * I_b1 * I_b2
You could of course also define different membrane voltage for each individual compartment.
Kind regards,
Charl
On Tue, Feb 18, 2020, at 22:20, Benedikt Rank wrote:
> Hello Jochen,
> thank you for your support!
>
> If I understand the connection topology correctly the distal
> compartment is connected to the proximal compartment which in turn is
> connected to the soma (d->p->s.)
> I am looking for a model with two separate dendritic compartments that
> are not interconnected yet both connect directly to the soma:
> branch1->soma<- branch2.
> Modelling the exact spatial relations, dimensions of compartments is
> not important to me.
>
> Potentially NestML is an alternative here.
> I have read the NestML language documentation but am not sure whether
> there are limitations imposed on the model esp. the update block.
> There is mainly three things I need:
> 1) topology (b1->s<-b2)
> 2)passing membrane voltages from branches to soma
> 3)multiplicative aggregation at soma
> Soma is essentially only integrating membrane voltages from the
> compartments in a multiplicative manner, ie. concurrent spike arrival
> at both compartments evoke significantly higher depolarizations of the
> membrane potential at soma.
> The soma then fires when a certain threshold is reached.
> Can this be done with NestML?
>
> Best,
> Benedikt
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