Support connections with heterogeneous synaptic time-constants

[arvoelke]

Is your feature request related to a problem? Please describe.

KerasSpiking supports using a different time-constant for each dimension (such that they can all be trained separately). But nengo.Connection(..., synapse=synapse) uses the same synapse for every dimension (in particular, the same time-constants). And there are lots of useful methods out there that use two or more time-constants, for example:

• https://pubmed.ncbi.nlm.nih.gov/19922294/
• https://www.frontiersin.org/articles/10.3389/fnins.2013.00153/full
• https://ieeexplore.ieee.org/document/7378880/

Describe the solution you'd like

At the API level, this could be implemented by allowing the time-constant(s) to be an array_like or Distribution. At the backend level, this could be implemented in the same way as KerasSpiking (i.e., by broadcasting the array of discretized time-constants onto the operations that concurrently update all of the synaptic state variables).

Describe alternatives you've considered

This is supported in nengolib by using a Node: https://arvoelke.github.io/nengolib-docs/nengolib.synapses.HeteroSynapse.html#nengolib.synapses.HeteroSynapse -- but this approach is really only useful for experimentation / prototyping. It's also a bit overkill, because it supports using synapses of all different types. More importantly, it doesn't help if you wanted to compile the network onto, say, Loihi (which supports heterogeneous time-constants). It also doesn't help if you wanted to convert a KerasSpiking model to Nengo.

[hunse]

Somewhat related to #1026/#1028 (allowing neuron time constants to be heterogeneous).

[drasmuss]

Notes from meeting: Only allow this on neuron-to-neuron connections (not NEF connections)