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

Research output: Contribution to journalArticlepeer-review

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

All Science Journal Classification (ASJC) codes

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

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