Alternation emerges as a multi-modal strategy for turbulent odor navigation
Abstract
Foraging mammals exhibit a familiar yet poorly characterized phenomenon, 'alternation', a pause to sniff in the air preceded by the animal rearing on its hind legs or raising its head. Rodents spontaneously alternate in the presence of airflow, suggesting that alternation serves an important role during plume-tracking. To test this hypothesis, we combine fully-resolved simulations of turbulent odor transport and Bellman optimization methods for decision-making under partial observability. We show that an agent trained to minimize search time in a realistic odor plume exhibits extensive alternation together with the characteristic cast-and-surge behavior observed in insects. Alternation is linked with casting and occurs more frequently far downwind of the source, where the likelihood of detecting airborne cues is higher relative to ground cues. Casting and alternation emerge as complementary tools for effective exploration with sparse cues. A model based on marginal value theory captures the interplay between casting, surging and alternation.
Data availability
All data generated or analyzed during this study are included in the manuscript and supporting file. The dataset with the simulation results has been made public at https://zenodo.org/record/6538177#.Yqrl_5BByJE
Article and author information
Author details
Funding
National Science Foundation (1764269)
- Gautam Reddy
European Research Council (101002724)
- Agnese Seminara
Air Force Office of Scientific Research (FA8655-20-1-7028)
- Agnese Seminara
NIH Office of the Director (R01DC018789)
- Agnese Seminara
National Science Foundation (PHY-1748958)
- Massimo Vergassola
Gordon and Betty Moore Foundation (2919.02)
- Gautam Reddy
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, Rigolli 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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- Computational and Systems Biology
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