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Moth olfactory receptor neurons adjust their encoding efficiency to temporal statistics of pheromone fluctuations

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  • Marie Levakova
  • Lubomir Kostal
  • Christelle Monsempès
  • Vincent Jacob
  • Philippe Lucas

Abstract

The efficient coding hypothesis predicts that sensory neurons adjust their coding resources to optimally represent the stimulus statistics of their environment. To test this prediction in the moth olfactory system, we have developed a stimulation protocol that mimics the natural temporal structure within a turbulent pheromone plume. We report that responses of antennal olfactory receptor neurons to pheromone encounters follow the temporal fluctuations in such a way that the most frequent stimulus timescales are encoded with maximum accuracy. We also observe that the average coding precision of the neurons adjusted to the stimulus-timescale statistics at a given distance from the pheromone source is higher than if the same encoding model is applied at a shorter, non-matching, distance. Finally, the coding accuracy profile and the stimulus-timescale distribution are related in the manner predicted by the information theory for the many-to-one convergence scenario of the moth peripheral sensory system.Author summary: Sensory neural systems of living organisms encode the representation of their environment with remarkable efficiency. We study the dynamic coding of naturalistic olfactory stimulation by pheromone-specific antennal neurons. The analysis reveals that the representation is optimal from several complementary information-theoretic perspectives. (1) Pheromone encounters are best detected if the concentration follows the naturally intermittent time course. (2) Antennal neurons dynamically adjust to the local stimulus statistics. (3) The coding accuracy profile and the stimulus-timescale distribution are in the relationship predicted by both information theory and statistical estimation theory.

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  • Marie Levakova & Lubomir Kostal & Christelle Monsempès & Vincent Jacob & Philippe Lucas, 2018. "Moth olfactory receptor neurons adjust their encoding efficiency to temporal statistics of pheromone fluctuations," PLOS Computational Biology, Public Library of Science, vol. 14(11), pages 1-17, November.
    • Handle: RePEc:plo:pcbi00:1006586
    DOI: 10.1371/journal.pcbi.1006586
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    References listed on IDEAS

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    1. Nicol S. Harper & David McAlpine, 2004. "Optimal neural population coding of an auditory spatial cue," Nature, Nature, vol. 430(7000), pages 682-686, August.
    2. Jean-Pierre Rospars & Alexandre Grémiaux & David Jarriault & Antoine Chaffiol & Christelle Monsempes & Nina Deisig & Sylvia Anton & Philippe Lucas & Dominique Martinez, 2014. "Heterogeneity and Convergence of Olfactory First-Order Neurons Account for the High Speed and Sensitivity of Second-Order Neurons," PLOS Computational Biology, Public Library of Science, vol. 10(12), pages 1-16, December.
    3. Lubomir Kostal & Petr Lansky & Jean-Pierre Rospars, 2008. "Efficient Olfactory Coding in the Pheromone Receptor Neuron of a Moth," PLOS Computational Biology, Public Library of Science, vol. 4(4), pages 1-11, April.
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    Cited by:

    1. Tomas Barta & Lubomir Kostal, 2019. "The effect of inhibition on rate code efficiency indicators," PLOS Computational Biology, Public Library of Science, vol. 15(12), pages 1-21, December.

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