Odor interactions and learning in a model of the insect antennal lobe

Alla Borisyuk, Brian H. Smith

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

We present a new model of insect antennal lobe in the form of integro-differential equation with short-range inhibition. The learning in the model modifies the odor-dependent input by adding a term that is proportional to the firing rates of the network in the pre-learning steady state. We study the modification of odor-induced spatial patterns (steady states) by combination of odors (binary mixtures) and learning. We show that this type of learning applied to the inhibitory network "increases the contrast" of the network's spatial activity patterns. We identify pattern modifications that could underlie insect behavioral phenomena.

Original languageEnglish (US)
Pages (from-to)1041-1047
Number of pages7
JournalNeurocomputing
Volume58-60
DOIs
StatePublished - Jun 1 2004
Externally publishedYes

Keywords

  • Antennal lobe
  • Integro-differential equations
  • Olfaction
  • Plasticity

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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