I am trying to build a network where one of the connection weights changes according to a
given function. I'm specifically looking for a step function, such that the weight
would stay constant at a negative value until a given time point, where it would suddenly
change to positive value. As far as I can tell, the existing synaptic models with
plasticity cannot do this.
I'm trying to do this in order to model a rebound effect, where a neuron fires after
being released form an inhibitory current. This effect takes place over a time scale of
seconds in the circuit I'm studying, so using an existing model with built-in
GABA-mediated rebound doesn't do the trick.
So is there a way to manually change a connection weight during the simulation? If not, is
there some other way I could achieve the same effect in NEST?
Thanks in advance!