Cognitive map-based navigation in wild bats revealed by a new high-throughput tracking system
收藏NIAID Data Ecosystem2026-03-11 收录
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http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.g4f4qrfn2
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Seven decades of research on the “cognitive map”, the allocentric representation of space, have yielded key neurobiological insights, yet we still lack field evidence from free-ranging wild animals. Using a system capable of tracking dozens of animals simultaneously at high accuracy and resolution, we assembled a large dataset of 172 foraging Egyptian fruit bats comprising >18M localizations collected over 3,449 bat-nights across 4 years. Detailed track analysis, combined with translocation experiments, revealed that wild bats seldom exhibit random search but instead repeatedly forage in goal-directed, long and straight flights that include frequent shortcuts. Alternative non-map-based strategies were ruled out by simulations, time-lag embedding and other trajectory analyses. Our results are consistent with expectations from cognitive map-like navigation and support previous neurobiological evidence from captive bats.
Methods
All bat procedures were approved by the Hebrew University of Jerusalem Animal Care and Use Committee (permit NS-15-14660-2). Bats were mist-netted on fruit trees or cave entrances and tagged with ATLAS in 38 capture sessions spanning all seasons between 2015-2019. Bats were tagged with ATLAS – a reverse-GPS system that localizes extremely light-weight, low-cost tags. Each ATLAS tag transmits a unique radio signal detected by a base-station network distributed in the study area. Tag localization is computed using nanosecond-scale differences in signal time-of-arrival to each station, enabling nearly real-time tracking and alleviating the need to retrieve the tag or to have some power-consuming remote-download capability. Bats were tagged by gluing the tag to their back (138 individuals) or by a custom-made collar (34 individuals). We applied a simple 10-second median filter to eliminate localization errors and smoothen the data.
创建时间:
2020-07-09



