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Effect of correlating adjacent neurons for identifying communications: Feasibility experiment in a cultured neuronal network

Authors
  • Nishitani, Yoshi
  • Hosokawa, Chie
  • Mizuno-Matsumoto, Yuko
  • Miyoshi, Tomomitsu
  • Tamura, Shinichi
Type
Published Article
Journal
AIMS Neuroscience
Publisher
AIMS Press
Publication Date
Dec 25, 2017
Volume
5
Issue
1
Pages
18–31
Identifiers
DOI: 10.3934/Neuroscience.2018.1.18
PMID: 32341949
PMCID: PMC7181895
Source
PubMed Central
Keywords
Disciplines
  • Research Article
License
Unknown

Abstract

Neuronal networks have fluctuating characteristics, unlike the stable characteristics seen in computers. The underlying mechanisms that drive reliable communication among neuronal networks and their ability to perform intelligible tasks remain unknown. Recently, in an attempt to resolve this issue, we showed that stimulated neurons communicate via spikes that propagate temporally, in the form of spike trains. We named this phenomenon “ spike wave propagation ”. In these previous studies, using neural networks cultured from rat hippocampal neurons, we found that multiple neurons, e.g. , 3 neurons, correlate to identify various spike wave propagations in a cultured neuronal network. Specifically, the number of classifiable neurons in the neuronal network increased through correlation of spike trains between current and adjacent neurons. Although we previously obtained similar findings through stimulation, here we report these observations on a physiological level. Considering that individual spike wave propagation corresponds to individual communication, a correlation between some adjacent neurons to improve the quality of communication classification in a neuronal network, similar to a diversity antenna, which is used to improve the quality of communication in artificial data communication systems, is suggested.

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