Echolocating bats often encounter clutter as they pursue insect prey. To probe the adaptive behaviors bats employ to mitigate the effects of clutter, this study quantified echolocation call features and head movements of big brown bats (Eptesicus fuscus) as they tracked a moving prey target in the dark. Bats were trained to rest on a perch and track an approaching target for a food reward. Clutter was positioned at different distances and angular offsets from the bat and the path of a moving target. This study hypothesized that bats dynamically adjust call features and head direction to facilitate target localization in the presence of clutter. The results show that bats shortened call duration and interval and increased head movements when the target was close to clutter. The study also revealed that bats increase the production of sonar strobe groups in cluttered environments, which may sharpen sonar spatial resolution. Spectral analysis showed that maximum call power shifted to lower frequencies when clutter was close to the target. These data demonstrate the big brown bat's range of adaptive behaviors that support target tracking in cluttered environments.
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Echolocating bats accumulate information from acoustic snapshots to predict auditory object motion
Unlike other predators that use vision as their primary sensory system, bats compute the three-dimensional (3D) position of flying insects from discrete echo snapshots, which raises questions about the strategies they employ to track and intercept erratically moving prey from interrupted sensory information. Here, we devised an ethologically inspired behavioral paradigm to directly test the hypothesis that echolocating bats build internal prediction models from dynamic acoustic stimuli to anticipate the future location of moving auditory targets. We quantified the direction of the bat’s head/sonar beam aim and echolocation call rate as it tracked a target that moved across its sonar field and applied mathematical models to differentiate between nonpredictive and predictive tracking behaviors. We discovered that big brown bats accumulate information across echo sequences to anticipate an auditory target’s future position. Further, when a moving target is hidden from view by an occluder during a portion of its trajectory, the bat continues to track its position using an internal model of the target’s motion path. Our findings also reveal that the bat increases sonar call rate when its prediction of target trajectory is violated by a sudden change in target velocity. This shows that the bat rapidly adapts its sonar behavior to update internal models of auditory target trajectories, which would enable tracking of evasive prey. Collectively, these results demonstrate that the echolocating big brown bat integrates acoustic snapshots over time to build prediction models of a moving auditory target’s trajectory and enable prey capture under conditions of uncertainty.
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- Award ID(s):
- 1734744
- PAR ID:
- 10200252
- Publisher / Repository:
- Proceedings of the National Academy of Sciences
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 117
- Issue:
- 46
- ISSN:
- 0027-8424
- Page Range / eLocation ID:
- p. 29229-29238
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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