Dynamic switching of neural codes in networks with gap junctions

Yuichi Katori; Naoki Masuda; Kazuyuki Aihara

doi:10.1016/j.neunet.2006.04.003

Dynamic switching of neural codes in networks with gap junctions

Yuichi Katori^*, Naoki Masuda, Kazuyuki Aihara

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

4 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 language	English
Pages (from-to)	1463-1466
Number of pages	4
Journal	Neural Networks
Volume	19
Issue number	10
DOIs	https://doi.org/10.1016/j.neunet.2006.04.003
Publication status	Published - 2006 Dec
Externally published	Yes

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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10.1016/j.neunet.2006.04.003

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@article{871059eb0e8442afbf587205a9cd8457,

title = "Dynamic switching of neural codes in networks with gap junctions",

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.",

keywords = "Chaotic itinerancy, Gap junction, Mutual information, Population rate coding, Synchrony, Temporal coding",

author = "Yuichi Katori and Naoki Masuda and Kazuyuki Aihara",

note = "Funding Information: One of the authors (KA) would like to thank K. Doya, H. Fujii, Y. Hirata, M. Kawato, E. Lang, S. Nara, N. Schweighofer, H. Suzuki, I. Tsuda, and M. Tsukada for their stimulating discussions on neural coding. This research is partially supported by Grant-in-Aid for Scientific Research on Priority Areas–System study on higher-order brain functions–from MEXT of Japan (17022012) and Special Postdoctoral Researchers Program of RIKEN.",

year = "2006",

month = dec,

doi = "10.1016/j.neunet.2006.04.003",

language = "English",

volume = "19",

pages = "1463--1466",

journal = "Neural Networks",

issn = "0893-6080",

publisher = "Elsevier Limited",

number = "10",

}

TY - JOUR

T1 - Dynamic switching of neural codes in networks with gap junctions

AU - Katori, Yuichi

AU - Masuda, Naoki

AU - Aihara, Kazuyuki

N1 - Funding Information: One of the authors (KA) would like to thank K. Doya, H. Fujii, Y. Hirata, M. Kawato, E. Lang, S. Nara, N. Schweighofer, H. Suzuki, I. Tsuda, and M. Tsukada for their stimulating discussions on neural coding. This research is partially supported by Grant-in-Aid for Scientific Research on Priority Areas–System study on higher-order brain functions–from MEXT of Japan (17022012) and Special Postdoctoral Researchers Program of RIKEN.

PY - 2006/12

Y1 - 2006/12

N2 - 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.

AB - 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.

KW - Chaotic itinerancy

KW - Gap junction

KW - Mutual information

KW - Population rate coding

KW - Synchrony

KW - Temporal coding

UR - http://www.scopus.com/inward/record.url?scp=33751231718&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33751231718&partnerID=8YFLogxK

U2 - 10.1016/j.neunet.2006.04.003

DO - 10.1016/j.neunet.2006.04.003

M3 - Article

C2 - 16887330

AN - SCOPUS:33751231718

SN - 0893-6080

VL - 19

SP - 1463

EP - 1466

JO - Neural Networks

JF - Neural Networks

IS - 10

ER -

Dynamic switching of neural codes in networks with gap junctions

Abstract

Keywords

ASJC Scopus subject areas

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