Sensing complementary temporal features of odor signals enhances navigation of diverse turbulent plumes

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

Abstract

We and others have shown that during odor plume navigation, walking Drosophila melanogaster bias their motion upwind in response to both the frequency of their encounters with the odor (Demir et al., 2020), and the intermittency of the odor signal, which we define to be the fraction of time the signal is above a detection threshold (Alvarez-Salvado et al., 2018). Here we combine and simplify previous mathematical models that recapitulated these data to investigate the benefits of sensing both of these temporal features, and how these benefits depend on the spatiotemporal statistics of the odor plume. Through agent-based simulations, we find that navigators that only use frequency or intermittency perform well in some environments - achieving maximal performance when gains are near those inferred from experiment - but fail in others. Robust performance across diverse environments requires both temporal modalities. However, we also find a steep tradeoff when using both sensors simultaneously, suggesting a strong benefit to modulating how much each sensor is weighted, rather than using both in a fixed combination across plumes. Finally, we show that the circuitry of the Drosophila olfactory periphery naturally enables simultaneous intermittency and frequency sensing, enhancing robust navigation through a diversity of odor environments. Together, our results suggest that the first stage of olfactory processing selects and encodes temporal features of odor signals critical to real-world navigation tasks.

Data availability

All data analyzed in this study are available from the original publications. Codes are available at https://github.com/emonetlab/plume-temporal-navigation

The following previously published data sets were used

Article and author information

Author details

  1. Viraaj Jayaram

    Department of Physics, Yale University, New Haven, United States
    Competing interests
    No competing interests declared.
  2. Nirag Kadakia

    Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9978-6450
  3. Thierry Emonet

    Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, United States
    For correspondence
    thierry.emonet@yale.edu
    Competing interests
    Thierry Emonet, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6746-6564

Funding

National Institutes of Health (F32MH118700)

  • Nirag Kadakia

National Institutes of Health (K99DC019397)

  • Nirag Kadakia

National Institutes of Health (R01GM106189)

  • Thierry Emonet

Yale University (Program in Physics,Engineering,and Biology)

  • Viraaj Jayaram

Sloan-Swartz Foundation

  • Nirag Kadakia

National Institutes of Health (R01GM138533)

  • Thierry Emonet

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

Copyright

© 2022, Jayaram 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.

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  1. Viraaj Jayaram
  2. Nirag Kadakia
  3. Thierry Emonet
(2022)
Sensing complementary temporal features of odor signals enhances navigation of diverse turbulent plumes
eLife 11:e72415.
https://doi.org/10.7554/eLife.72415

Share this article

https://doi.org/10.7554/eLife.72415

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