Emergent behavior and neural dynamics in artificial agents tracking turbulent plumes

Jewell

2022

J. R. Soc. Interface.

Estimating the direction of ambient fluid flow is a crucial step during chemical plume tracking for flying and swimming animals. How animals accomplish this remains an open area of investigation. Recent calcium imaging with tethered flying Drosophila has shown that flies encode the angular direction of multiple sensory modalities in their central complex: orientation, apparent wind (or airspeed) direction and direction of motion. Here, we describe a general framework for how these three sensory modalities can be integrated over time to provide a continuous estimate of ambient wind direction. After validating our framework using a flying drone, we use simulations to show that ambient wind direction can be most accurately estimated with trajectories characterized by frequent, large magnitude turns. Furthermore, sensory measurements and estimates of their derivatives must be integrated over a period of time that incorporates at least one of these turns. Finally, we discuss approaches that insects might use to simplify the required computations, and present a list of testable predictions. Together, our results suggest that ambient flow estimation may be an important driver underlying the zigzagging manoeuvres characteristic of plume tracking animals’ trajectories.

Section: Zigzag Manoeuvres Optimize Wind Direction Estimationmentioning

confidence: 99%

Active anemosensing hypothesis: how flying insects could estimate ambient wind direction through sensory integration and active movement

Jewell

2022

J. R. Soc. Interface.

“…Under such conditions odor plumes will be more dispersed and meandering, and the canonical cast-and-surge behavior that insects employ in laminar wind conditions [59, 3] is unlikely to be effective. Instead, insects may need to rely on a time history of odor and wind information [43, 60, 61], or a different strategy altogether. Discovering what these strategies are will require controlled laboratory settings in novel wind tunnel assays where directional variability can be controlled to match the linear relationship with turbulent intensity that we describe in Figure 3E-F.…”

Section: Discussionmentioning

confidence: 99%

Near-surface wind variability over spatiotemporal scales relevant to plume tracking insects

2023

Preprint

Odor plume tracking is an important biological process for many organisms, and flying insects have served as popular model systems for studying these behaviors both in the field and in lab settings. The shape and statistics of the airborne odor plumes that insects follow are largely governed by the wind that advects them. Prior atmospheric studies have investigated aspects of microscale wind patterns with an emphasis on characterizing pollution dispersion, enhancing weather prediction models, and for assessing wind energy potential. Here, we aim to characterize microscale wind dynamics through the lens of short-term ecological functions by focusing on spatial and temporal scales most relevant to an insect actively searching for an odor source. We collected and compared near-surface wind data across three distinct environments (sage steppe, forest, and urban) in locations across Northern Nevada. Our findings show that near-surface wind direction variability decreases with increasing wind speeds and increases in environments with greater surface complexity. Across environments, there is a strong correlation between the variability in wind speed (i.e. turbulence intensity) and wind direction (i.e. the standard deviation in wind direction). In some environments, the standard deviation in wind direction varied as much as 15 deg to 75 deg on time scales of 1-10 minutes. We draw insights between our findings and previous plume tracking experiments to provide a general intuition for future field research and guidance for wind tunnel experimental design. From our analyses, we hypothesize that there may be an ideal range of wind speeds and environment complexity in which insects will be most successful when tracking an odor plume to its source.

“…Furthermore, in some efforts to reverse engineer plume tracking strategies using an “optimal” reinforcement learning framework for agents that are provided with ambient wind direction information, the distinctive casting exhibited by animals appears to be largely absent [42], or diminished when the agent is inside the plume [43]. These findings together with our results presented here suggest that the zigzagging exhibited by flying insects, and likely other flying and swimming animals too, is crucial for them to estimate the ambient wind direction in order to guide plume tracking decisions.…”

Section: Discussionmentioning

confidence: 99%

Active Anemosensing Hypothesis: How Flying Insects Could Estimate Ambient Wind Direction Through Sensory Integration & Active Movement

Jewell

2022

Preprint

Estimating the direction of ambient fluid flow is a crucial step during chemical plume tracking for flying and swimming animals. How animals accomplish this remains an open area of investigation. Recent calcium imaging with tethered flying Drosophila has shown that flies encode the angular direction of multiple sensory modalities in their central complex: orientation, apparent wind (or airspeed) direction, and direction of. Here we describe a general framework for how these three sensory modalities can be integrated over time to provide a continuous estimate of ambient wind direction. After validating our framework using a flying drone, we use simulations to show that ambient wind direction can be most accurately estimated with trajectories characterized by frequent, large magnitude turns. Furthermore, sensory measurements and estimates of their derivatives must be integrated over a period of time that incorporates at least one of these turns. Finally, we discuss approaches that insects might use to simplify the required computations, and present a list of testable predictions. Together, our results suggest that ambient flow estimation may be an important driver underlying the zigzagging maneuvers characteristic of plume tracking animals' trajectories.