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

Alla Borisyuk, Brian Smith

Research output: Contribution to journalArticle

3 Citations (Scopus)

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 2004
Externally publishedYes

Fingerprint

Odors
Insects
Learning
Integrodifferential equations
Binary mixtures
Odorants

Keywords

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

ASJC Scopus subject areas

  • Artificial Intelligence
  • Cellular and Molecular Neuroscience

Cite this

Odor interactions and learning in a model of the insect antennal lobe. / Borisyuk, Alla; Smith, Brian.

In: Neurocomputing, Vol. 58-60, 06.2004, p. 1041-1047.

Research output: Contribution to journalArticle

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