Computational Architecture of the Granular Layer of Cerebellum-Like Structures

The Cerebellum
Peter BratbyJohn Montgomery

Abstract

In the adaptive filter model of the cerebellum, the granular layer performs a recoding which expands incoming mossy fibre signals into a temporally diverse set of basis signals. The underlying neural mechanism is not well understood, although various mechanisms have been proposed, including delay lines, spectral timing and echo state networks. Here, we develop a computational simulation based on a network of leaky integrator neurons, and an adaptive filter performance measure, which allows candidate mechanisms to be compared. We demonstrate that increasing the circuit complexity improves adaptive filter performance, and relate this to evolutionary innovations in the cerebellum and cerebellum-like structures in sharks and electric fish. We show how recurrence enables an increase in basis signal duration, which suggest a possible explanation for the explosion in granule cell numbers in the mammalian cerebellum.

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Citations

Aug 21, 2016·The Cerebellum·Peter BratbyJohn Montgomery
Apr 28, 2017·Journal of Neurophysiology·Reinoud Maex, Boris Gutkin
Jan 29, 2019·Frontiers in Computational Neuroscience·Hari Teja KalidindiEgidio Falotico

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