Neural heterogeneity promotes robust learning
Schedule
Friday, January 22, 2021
16:00 UTC
Dan Goodman
Prof
Imperial College London
Host: The Neurotheory Forum
Recording
Open recording
Event Information
Recording
Available
Host
The Neurotheory Forum
Duration
70 minutes
Abstract
The brain has a hugely diverse, heterogeneous structure. By contrast, many functional neural models are homogeneous. We compared the performance of spiking neural networks trained to carry out difficult tasks, with varying degrees of heterogeneity. Introducing heterogeneity in membrane and synapse time constants substantially improved task performance, and made learning more stable and robust across multiple training methods, particularly for tasks with a rich temporal structure. In addition, the distribution of time constants in the trained networks closely matches those observed experimentally. We suggest that the heterogeneity observed in the brain may be more than just the byproduct of noisy processes, but rather may serve an active and important role in allowing animals to learn in changing environments.
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