More generally, we should look more carefully at profiling decode neurons (formerly called "interneurons") under a wide variety of conditions (frequency, tau, dynamic range, number of neurons), and characterize / identify their dynamical behaviour, so that we may improve these methods and optimize their parameters.
This is motivated in part by the following TODOs:
https://github.com/nengo/nengo-loihi/blob/1517915baa1b0200e5241ba55a65e9d0bc09bff8/nengo_loihi/decode_neurons.py#L296-L298
https://github.com/nengo/nengo-loihi/blob/1517915baa1b0200e5241ba55a65e9d0bc09bff8/nengo_loihi/decode_neurons.py#L264-L266
More generally, we should look more carefully at profiling decode neurons (formerly called "interneurons") under a wide variety of conditions (frequency, tau, dynamic range, number of neurons), and characterize / identify their dynamical behaviour, so that we may improve these methods and optimize their parameters.