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

Abstract
Data availability
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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

1. Demir M
2. Kadakia N
3. Anderson H
4. Clark D
5. Emonet T
(2020) Data presented in "Walking Drosophila navigate complex plumes using stochastic decisions biased by the timing of odor encounters"
https://creativecommons.org/publicdomain/zero/1.0/.

https://doi.org/10.5061/dryad.4j0zpc87z
1. Álvarez-Salvado E
2. Licata A
3. Connor E
4. McHugh M
5. King B
6. Stavropoulos N
7. Victor J
8. Crimaldi J
9. Nagel K
10. King B
(2020) Data from: Elementary sensory-motor transformations underlying olfactory navigation in walking fruit flies
https://creativecommons.org/publicdomain/zero/1.0/.

https://doi.org/10.5061/dryad.g27mq71

Article and author information

Author details

Viraaj Jayaram

Department of Physics, Yale University, New Haven, United States

Competing interests
No competing interests declared.
Nirag Kadakia

Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, United States

Competing interests
No competing interests declared.

"This ORCID iD identifies the author of this article:" 0000-0001-9978-6450
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.

"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

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.