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The Voice of Bats: How Greater Mouse-eared Bats Recognize Individuals Based on Their Echolocation Calls

Overview of attention for article published in PLoS Computational Biology, June 2009
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Title
The Voice of Bats: How Greater Mouse-eared Bats Recognize Individuals Based on Their Echolocation Calls
Published in
PLoS Computational Biology, June 2009
DOI 10.1371/journal.pcbi.1000400
Pubmed ID
Authors

Yossi Yovel, Mariana Laura Melcon, Matthias O. Franz, Annette Denzinger, Hans-Ulrich Schnitzler

Abstract

Echolocating bats use the echoes from their echolocation calls to perceive their surroundings. The ability to use these continuously emitted calls, whose main function is not communication, for recognition of individual conspecifics might facilitate many of the social behaviours observed in bats. Several studies of individual-specific information in echolocation calls found some evidence for its existence but did not quantify or explain it. We used a direct paradigm to show that greater mouse-eared bats (Myotis myotis) can easily discriminate between individuals based on their echolocation calls and that they can generalize their knowledge to discriminate new individuals that they were not trained to recognize. We conclude that, despite their high variability, broadband bat-echolocation calls contain individual-specific information that is sufficient for recognition. An analysis of the call spectra showed that formant-related features are suitable cues for individual recognition. As a model for the bat's decision strategy, we trained nonlinear statistical classifiers to reproduce the behaviour of the bats, namely to repeat correct and incorrect decisions of the bats. The comparison of the bats with the model strongly implies that the bats are using a prototype classification approach: they learn the average call characteristics of individuals and use them as a reference for classification.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 220 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 6 3%
Brazil 3 1%
Canada 2 <1%
United Kingdom 2 <1%
Israel 2 <1%
Netherlands 1 <1%
France 1 <1%
Portugal 1 <1%
Bulgaria 1 <1%
Other 5 2%
Unknown 196 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 48 22%
Student > Ph. D. Student 47 21%
Student > Master 28 13%
Student > Bachelor 18 8%
Other 16 7%
Other 42 19%
Unknown 21 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 146 66%
Environmental Science 20 9%
Neuroscience 10 5%
Computer Science 6 3%
Engineering 4 2%
Other 9 4%
Unknown 25 11%