Front-end Weber-Fechner gain control enhances the fidelity of combinatorial odor coding

  1. Nirag Kadakia
  2. Thierry Emonet  Is a corresponding author
  1. Yale University, United States

Abstract

We showed previously (Gorur-Shandilya et al 2017) that Drosophila olfactory receptor neurons (ORNs) expressing the co-receptor Orco scale their gain inversely with mean odor intensity according to Weber-Fechner's law. Here we show that this front-end adaptation promotes the reconstruction of odor identity from dynamic odor signals, even in the presence of confounding background odors and rapid intensity fluctuations. These enhancements are further aided by known downstream transformations in the antennal lobe and mushroom body. Our results, which are applicable to various odor classification and reconstruction schemes, stem from the fact that this adaptation mechanism is not intrinsic to the identity of the receptor involved. Instead, a feedback mechanism adjusts receptor sensitivity based on the activity of the receptor-Orco complex, according to Weber-Fechner's law. Thus, a common scaling of the gain across Orco-expressing ORNs may be a key feature of ORN adaptation that helps preserve combinatorial odor codes in naturalistic landscapes.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. All software codes are available via GitHub (https://github.com/emonetlab/ORN-WL-gain-control).

Article and author information

Author details

  1. Nirag Kadakia

    Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9978-6450
  2. Thierry Emonet

    Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, United States
    For correspondence
    thierry.emonet@yale.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6746-6564

Funding

Swartz Foundation (Postdoctoral Fellowship)

  • Nirag Kadakia

National Institutes of Health (R01 GM106189)

  • Thierry Emonet

National Institute of Mental Health (F32 MH118700)

  • Nirag Kadakia

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2019, Kadakia & Emonet

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Nirag Kadakia
  2. Thierry Emonet
(2019)
Front-end Weber-Fechner gain control enhances the fidelity of combinatorial odor coding
eLife 8:e45293.
https://doi.org/10.7554/eLife.45293

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https://doi.org/10.7554/eLife.45293