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Would be great if we had functions to easily connect neurons directly, by specifying the dynamics of the synapse and (in the case of phenomenological models) specifying to which compartment the synapse goes.
For Networks this could be extended so that one can use an adjacency matrix / probability of connection presence, or loop over all the neurons and specify the connection between individual pairs.
The text was updated successfully, but these errors were encountered:
I've thought about the subcompartment addressing--we can solve this by adding metadata to network nodes which hold "parent_id" and "subindex". Directed edges then run from output (index 0) to target compartments.
There is API support for specifying connections between neurons but we should have better support for taking an adjacency matrix as input. The performance scaling of add_synapse! is rather poor, too.
Would be great if we had functions to easily connect neurons directly, by specifying the dynamics of the synapse and (in the case of phenomenological models) specifying to which compartment the synapse goes.
For
Network
s this could be extended so that one can use an adjacency matrix / probability of connection presence, or loop over all the neurons and specify the connection between individual pairs.The text was updated successfully, but these errors were encountered: