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Open Access

Stimulus-onset asynchrony can aid odor segregation

  • Thomas Nowotny1,
  • C Giovanni Galizia2 and
  • Paul Szyszka2
Flavour20143(Suppl 1):P12

https://doi.org/10.1186/2044-7248-3-S1-P12

Published: 16 April 2014

Insects have a remarkable ability to identify and track odor sources in multi-odor backgrounds. Recent behavioral experiments show that this ability relies on detecting millisecond stimulus asynchronies between odors that originate from different sources [1]. Honeybees are able to distinguish mixtures where both odors arrive at the same time (synchronous mixtures) from those where odor onsets are staggered (asynchronous mixtures) even if the delay is only a few milliseconds.

On this poster we explore asynchronous mixture recognition in a model of the honeybee antennal lobe. We demonstrate how local neuronal processing can translate the small onset time difference into lasting differences in the response pattern in the antennal lobe and hypothesize that a mechanism of this kind could facilitate odor-background segregation in downstream circuits of the olfactory pathway. We present a detailed data-driven model of the bee antennal lobe that reproduces a large data set of experimentally observed odor responses [2] and demonstrate with this model that our hypothesis is consistent with the current knowledge of the olfactory circuits in the bee brain.

Authors’ Affiliations

(1)
CCNR, School of Engineering and Informatics, University of Sussex
(2)
Fachbereich Biologie, Universität Konstanz

References

  1. Szyszka P, Stierle JS, Biergans S, Galizia CG: The Speed of Smell: Odor-Object Segregation within Milliseconds. PLoS One. 2012, 7: e36096-PubMed CentralView ArticlePubMedGoogle Scholar
  2. Ditzen M: Odor concentration and identity coding in the antennal lobe of the honeybee Apis mellifera. Ph.D. thesis. 2005, Freie Universität Berlin. BerlinGoogle Scholar

Copyright

© Nowotny et al; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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