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Complex echo classification by echo-locating bats: A review

  • Yossi Yovel*
  • , Matthias O. Franz
  • , Peter Stilz
  • , Hans Ulrich Schnitzler
  • *Corresponding author for this work
  • Weizmann Institute of Science
  • University of Tübingen
  • Konstanz University of Applied Sciences

Research output: Contribution to journalReview articlepeer-review

40 Scopus citations

Abstract

Echo-locating bats constantly emit ultrasonic pulses and analyze the returning echoes to detect, localize, and classify objects in their surroundings. Echo classification is essential for bats' everyday life; for instance, it enables bats to use acoustical landmarks for navigation and to recognize food sources from other objects. Most of the research of echo based object classification in echo-locating bats was done in the context of simple artificial objects. These objects might represent prey, flower, or fruit and are characterized by simple echoes with a single up to several reflectors. Bats, however, must also be able to use echoes that return from complex structures such as plants or other types of background. Such echoes are characterized by superpositions of many reflections that can only be described using a stochastic statistical approach. Scientists have only lately started to address the issue of complex echo classification by echo-locating bats. Some behavioral evidence showing that bats can classify complex echoes has been accumulated and several hypotheses have been suggested as to how they do so. Here, we present a first review of this data. We raise some hypotheses regarding possible interpretations of the data and point out necessary future directions that should be pursued.

Original languageEnglish
Pages (from-to)475-490
Number of pages16
JournalJournal of Comparative Physiology A: Neuroethology, Sensory, Neural, and Behavioral Physiology
Volume197
Issue number5
DOIs
StatePublished - May 2011
Externally publishedYes

Funding

FundersFunder number
Graduiertenkolleg NeurobiologieSCHN 138/27-1
University of Applied SciencesMEST-CT-2004-504321
European Commission
Deutsche Forschungsgemeinschaft

    Keywords

    • Bat
    • Behavior
    • Classification
    • Echolocation
    • Statistics

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