Chaos may enhance expressivity in cerebellar granular layer

Keita Tokuda, Naoya Fujiwara, Akihito Sudo, Yuichi Katori

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)72-86
Number of pages15
JournalNeural Networks
Volume136
DOIs
Publication statusPublished - 2021 Apr

Keywords

  • Cerebellar granular layer
  • Chaotic dynamics
  • Gap junction
  • Reaction–diffusion system
  • Reservoir computing
  • Sierpinski gasket

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Artificial Intelligence

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