Chaos may enhance expressivity in cerebellar granular layer

TL;DR

This paper proposes that the dense gap junctions between Golgi cells in the cerebellar granular layer induce chaotic dynamics, enhancing the layer's representational complexity and temporal processing capabilities, demonstrated through a computational model.

Contribution

It introduces a novel model showing how gap junction-induced chaos in Golgi cells enhances the cerebellar granular layer's expressivity and temporal encoding abilities.

Findings

Chaotic dynamics produce complex, frequency-rich output patterns.

Reservoir dynamics encode passage of time from inputs.

Spatial inputs are mapped to diverse temporal patterns.

Abstract

Recent evidence suggests that Golgi cells in the cerebellar granular layer are densely connected to each other with massive gap junctions. Here, we propose that the massive gap junctions between the Golgi cells contribute to the representational complexity of the granular layer of the cerebellum by inducing chaotic dynamics. We construct a model of cerebellar granular layer with diffusion coupling through gap junctions between the Golgi cells, and evaluate the representational capability of the network with the reservoir computing framework. First, we show that the chaotic dynamics induced by diffusion coupling results in complex output patterns containing a wide range of frequency components. Second, the long non-recursive time series of the reservoir represents the passage of time from an external input. These properties of the reservoir enable mapping different spatial inputs into different temporal patterns.