A new classification of neuron models for random inputs on bifurcation structures

Ryosuke Hosaka, Tohru Ikeguchi, Yutaka Sakai, Shuji Yoshizawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cortical regularly spiking neurons are classified into two classes, Class I and Class II, by their firing frequencies. We investigated the statistical characteristics of spike sequences of Class I and II neurons stimulated by uncorrelated fluctuations by two interspike interval statistics; coefficient of variation and coefficient of skewness. As a result, the interspike interval statistics of Class I and II neurons are different. Moreover, even if the neurons belong to the same class, if the precise bifurcation structures of the neurons are different, the statistics exhibit different characteristics. The results indicate insufficiency to classify neurons by the firing frequencies and necessity to classify neurons by the precise bifurcation structures.

Original languageEnglish
Title of host publicationISCAS 2006
Subtitle of host publication2006 IEEE International Symposium on Circuits and Systems, Proceedings
Pages2741-2744
Number of pages4
Publication statusPublished - 2006
Externally publishedYes
EventISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems - Kos, Greece
Duration: 2006 May 212006 May 24

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Conference

ConferenceISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems
Country/TerritoryGreece
CityKos
Period06/5/2106/5/24

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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