1. Computational and Systems Biology
  2. Neuroscience
Download icon

Olfactory receptor neurons use gain control and complementary kinetics to encode intermittent odorant stimuli

  1. Srinivas Gorur-Shandilya
  2. Mahmut Demir
  3. Junjiajia Long
  4. Damon A Clark
  5. Thierry Emonet  Is a corresponding author
  1. Yale University, United States
Research Article
  • Cited 18
  • Views 2,048
  • Annotations
Cite this article as: eLife 2017;6:e27670 doi: 10.7554/eLife.27670

Abstract

Insects find food and mates by navigating odorant plumes that can be highly intermittent, with intensities and durations that vary rapidly over orders of magnitude. Much is known about olfactory responses to pulses and steps, but it remains unclear how olfactory receptor neurons (ORNs) detect the intensity and timing of natural stimuli, where the absence of scale in the signal makes detection a formidable olfactory task. By stimulating Drosophila ORNs in vivo with naturalistic and Gaussian stimuli, we show that ORNs adapt to stimulus mean and variance, and that adaptation and saturation contribute to naturalistic sensing. Mean-dependent gain control followed the Weber-Fechner relation and occurred primarily at odor transduction, while variance-dependent gain control occurred at both transduction and spiking. Transduction and spike generation possessed complementary kinetic properties, that together preserved the timing of odorant encounters in ORN spiking, regardless of intensity. Such scale-invariance could be critical during odor plume navigation.

Article and author information

Author details

  1. Srinivas Gorur-Shandilya

    Interdepartmental Neuroscience Program, 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:" 0000-0002-7429-457X

  2. Mahmut Demir

    Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Junjiajia Long

    Department of Physics, Yale University, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.

  4. Damon A Clark

    Interdepartmental Neuroscience Program, 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:" 0000-0001-8487-700X

  5. Thierry Emonet

    Interdepartmental Neuroscience Program, 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

Whitehall Foundation

  • Srinivas Gorur-Shandilya
  • Mahmut Demir
  • Thierry Emonet

Sloan Research Fellowship

  • Damon A Clark

Searle Scholar Award

  • Damon A Clark

Smith Family Foundation

  • Damon A Clark

Natural Sciences and Engineering Research Council of Canada (PGSD2-471587-2015)

  • Junjiajia Long

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

Reviewing Editor

  1. Fred Rieke, Howard Hughes Medical Institute, University of Washington, United States

Publication history

  1. Received: April 10, 2017
  2. Accepted: June 26, 2017
  3. Accepted Manuscript published: June 27, 2017 (version 1)
  4. Accepted Manuscript updated: June 28, 2017 (version 2)
  5. Version of Record published: July 24, 2017 (version 3)

Copyright

© 2017, Gorur-Shandilya et al.

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.

Metrics

  • 2,048
    Page views
  • 413
    Downloads
  • 18
    Citations

Article citation count generated by polling the highest count across the following sources: Scopus, Crossref, PubMed Central.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Categories and tags

Research organism

Further reading

    1. Computational and Systems Biology
    2. Neuroscience

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

    Nirag Kadakia, Thierry Emonet
    Research Advance Updated

    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.

    1. Computational and Systems Biology
    2. Neuroscience

    Sodium channels implement a molecular leaky integrator that detects action potentials and regulates neuronal firing

    Marco A Navarro et al.
    Research Article
    1. Computational and Systems Biology
    2. Developmental Biology

    Analysis of zebrafish periderm enhancers facilitates identification of a regulatory variant near human KRT8/18

    Huan Liu et al.
    Research Article Updated