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Odorant mixtures elicit less variable and faster responses than pure odorants

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posted on 2023-06-12, 07:27 authored by Ho Ka Chan, Fabian Hersperger, Emiliano Marachlian, Brian H Smith, Fernando Locatelli, Paul Szyszka, Thomas NowotnyThomas Nowotny
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.

History

Publication status

  • Published

File Version

  • Published version

Journal

PLoS Computational Biology

ISSN

1553-734X

Publisher

Public Library of Science

Issue

12

Volume

14

Page range

1-27

Article number

e1006536

Department affiliated with

  • Informatics Publications

Research groups affiliated with

  • Centre for Computational Neuroscience and Robotics Publications
  • Sussex Neuroscience Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2018-10-17

First Open Access (FOA) Date

2018-12-13

First Compliant Deposit (FCD) Date

2018-10-17

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