Chaotic itinerancy, temporal segmentation and spatio-temporal combinatorial codes

Juliana R. Dias, Rodrigo F. Oliveira, Osame Kinouchi

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


We study a deterministic dynamics with two time scales in a continuous state attractor network. To the usual (fast) relaxation dynamics towards point attractors ("patterns") we add a slow coupling dynamics that makes the visited patterns lose stability, leading to an itinerant behavior in the form of punctuated equilibria. One finds that the transition frequency matrix for transitions between patterns shows non-trivial statistical properties in the chaotic itinerant regime. We show that mixture input patterns can be temporally segmented by the itinerant dynamics. The viability of a combinatorial spatio-temporal neural code is also demonstrated.

Original languageEnglish (US)
Pages (from-to)1-5
Number of pages5
JournalPhysica D: Nonlinear Phenomena
Issue number1
StatePublished - Jan 1 2008
Externally publishedYes

All Science Journal Classification (ASJC) codes

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


  • Chaotic itinerancy
  • Combinatorial codes
  • Neural codes
  • Neural networks
  • Olfactory system
  • Sensory systems


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