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Neural heterogeneity promotes robust learning

Date: Friday, January 22, 2021 16:00 - 17:00
Speaker: Dan Goodman (Imperial College London)
Location: Online
Series: Neurotheory Forum
Host: Everton Agnes
Contact: IST Austria / University of Oxford

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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