The inertial-DNF model: Spatiotemporal coding on two time scales

Orit Kliper, David Horn, Brigitte Quenet

Research output: Contribution to journalArticlepeer-review

Abstract

We introduce the inertial-DNF (iDNF) model, an expansion of the dynamic neural filter (DNF) model, a model generating spatiotemporal patterns similar to those observed in the locust antennal lobes (ALs). The DNF model, which was described in previous works, includes one temporal scale defining the discrete dynamics inherent to the model. It lacks a second, slow, temporal scale that exists in the biological spatiotemporal data, where one finds slow temporal patterns of individual neurons in response to odor. Using the iDNF, we examine mechanisms that lead to temporal ordered spatiotemporal patterns, similar to those observed in the experimental data. We conclude that a second temporal scale is crucial for the creation of temporal order within the evolving spatiotemporal pattern.

Original languageEnglish
Pages (from-to)543-548
Number of pages6
JournalNeurocomputing
Volume65-66
Issue numberSPEC. ISS.
DOIs
StatePublished - Jun 2005

Keywords

  • Dynamic neural filter
  • Inertia
  • Olfaction
  • Recurrent network
  • Temporal coding

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