Odorant mixtures elicit less variable and faster responses than pure odorants

Chan, Ho Ka, Hersperger, Fabian, Marachlian, Emiliano, Smith, Brian H, Locatelli, Fernando, Szyszka, Paul and Nowotny, Thomas (2018) Odorant mixtures elicit less variable and faster responses than pure odorants. PLoS Computational Biology. ISSN 1553-734X

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Abstract

In natural environments, odors are typically mixtures of several different chemical compounds. However, the implications of mixtures for odor processing have not been fully investigated. We have extended a standard olfactory receptor model to mixtures and found through its mathematical analysis that odorant-evoked activity patterns are more stable across concentrations and first-spike latencies of receptor neurons are shorter for mixtures than for pure odorants. Shorter first-spike latencies arise from the nonlinear dependence of binding rate on odorant concentration, commonly described by the Hill coefficient, while the more stable activity patterns result from the competition between different ligands for receptor sites. These results are consistent with observations from numerical simulations and physiological recordings in the olfactory system of insects. Our results suggest that mixtures allow faster and more reliable olfactory coding, which could be one of the reasons why animals often use mixtures in chemical signaling.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Informatics
Research Centres and Groups: Centre for Computational Neuroscience and Robotics
Sussex Neuroscience
Depositing User: Lucy Arnold
Date Deposited: 17 Oct 2018 09:06
Last Modified: 13 Dec 2018 17:21
URI: http://srodev.sussex.ac.uk/id/eprint/79531

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