Dynamic switching of neural codes in networks with gap junctions

Yuichi Katori, Naoki Masuda, Kazuyuki Aihara

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Population rate coding and temporal coding are common neural codes. Recent studies suggest that these two codes may be alternatively used in one neural system. Based on the fact that there are massive gap junctions in the brain, we explore how this switching behavior may be related to neural codes in networks of neurons connected by gap junctions. First, we show that under time-varying inputs, such neural networks show switching between synchronous and asynchronous states. Then, we quantify network dynamics by three mutual information measures to show that population rate coding carries more information in asynchronous states and temporal coding does so in synchronous states.

Original languageEnglish
Pages (from-to)1463-1466
Number of pages4
JournalNeural Networks
Volume19
Issue number10
DOIs
Publication statusPublished - 2006 Dec
Externally publishedYes

Keywords

  • Chaotic itinerancy
  • Gap junction
  • Mutual information
  • Population rate coding
  • Synchrony
  • Temporal coding

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Artificial Intelligence

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