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Cognitive map-based navigation in wild bats revealed by a new high-throughput tracking system

Cite this dataset

Shohami, David; Nathan, Ran (2020). Cognitive map-based navigation in wild bats revealed by a new high-throughput tracking system [Dataset]. Dryad.


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. 


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.

Usage notes

The data are in a comma-delimited text file. Each row is a single localization of a single tag. There are 10 columns, as follows:

1) Tag (bat) number

2) X-coordinate (metric, ITM coordinate system)

3) Y-coordinate (metric, ITM coordinate system)

4) Timestamp (Unix epoch time) in UTC

5-10) Time in human-readable format: Year, Month, Day, Hour, Minute, Second



Minerva Center for Movement Ecology, Hebrew University of Jerusalem

Minerva Stiftung

Israel Science Foundation, Award: 965/15

Israel Science Foundation, Award: I-1316-413.13/2015

Israel Science Foundation, Award: 1259/09

Israel Science Foundation, Award: 1316/05