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Richer network dynamics of intrinsically non-regular neurons measured through mutual information

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 2084 LNCS, Issue: PART 1, Page: 490-497
2001
  • 2
    Citations
  • 0
    Usage
  • 10
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    2
    • Citation Indexes
      2
  • Captures
    10

Conference Paper Description

Central Pattern Generators (CPGs) are assemblies of neurons that act cooperatively to produce regular signals to motor systems. The individual behavior of some members of the CPGs has often been observed as highly variable spiking-bursting activity. In spite of this fact, the collective behavior of the intact CPG produces always regular rhythmic activity. In this paper we show that simple networks built out of intrinsically non-regular units can display modes of regular collective behavior not observed in networks composed of intrinsically regular neurons. Using a measure of mutual information we characterize several patterns of activity observed by changing the coupling strength and the network topology. We show that the cooperative behavior of these neurons can display a rich variety of information transfer while maintaining the regularity of the rhythms. © Springer-Verlag Berlin Heidelberg 2001.

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