Differentiation and clustering in a self-organization process of model neurons

Research output: Contribution to journalArticle

Abstract

A globally coupled model and a tree-structured model are proposed to study the self-organization in neural networks. The neuron population receives uniformly distributed inputs, but as a result of dynamic instability the population is differentiated into several clusters which respond to the respective specific inputs strongly.

Original languageEnglish
Pages (from-to)26-32
Number of pages7
JournalPhysica D: Nonlinear Phenomena
Volume98
Issue number1
DOIs
Publication statusPublished - Jan 1 1996
Externally publishedYes

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All Science Journal Classification (ASJC) codes

  • Statistical and Nonlinear Physics
  • Mathematical Physics
  • Condensed Matter Physics
  • Applied Mathematics

Cite this

Differentiation and clustering in a self-organization process of model neurons. / Sakaguchi, Hidetsugu.

In: Physica D: Nonlinear Phenomena, Vol. 98, No. 1, 01.01.1996, p. 26-32.

Research output: Contribution to journalArticle

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