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Hi,
I would like to model a neuron that has a fixed number of receptors with same synaptic dynamics model, but different parameters. These receptors are AlignPost. I considered splitting out connection matrix for each receptor, or alternatively having dummy neuron groups. But they seem less convenient. So right now, I flatten out receptors and post neurons, and use something like this,
class CUBAMultiReceptor(bp.dyn.CUBA):
def __init__(
self,
n_receptors: int = 1,
name: Optional[str] = None,
scaling: Optional[bm.Scaling] = None,
):
super().__init__(name=name, scaling=scaling)
self.n_receptors = n_receptors
def update(self, conductance, potential=None):
conductance = super().update(conductance, potential)
return bm.ein_reduce(
conductance,
"... (neuron receptor) -> ... neuron",
receptor=self.n_receptors,
reduction="sum",
)
This will require STDP_Song2000 to be modified accordingly to propagate post spikes. I wonder if there are better solutions?
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