Journal of Comparative Physiology A

, Volume 197, Issue 5, pp 475–490 | Cite as

Complex echo classification by echo-locating bats: a review

  • Yossi Yovel
  • Matthias O. Franz
  • Peter Stilz
  • Hans-Ulrich Schnitzler


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.


Echolocation Classification Bat Statistics Behavior 



We would like to thank R. Boonman for the fruitful discussion and our two anonymous reviewers for their comments. This work was funded by SFB 550, by the Graduiertenkolleg Neurobiologie, and by grant SCHN 138/27-1 of the German Science Foundation. The work was also supported by the University of Applied Sciences at Konstanz, Germany. This work was also supported by the human resources and mobility activity Marie Curie host fellowships for early stage research training under contract MEST-CT-2004-504321 PERACT by the European Union.


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Yossi Yovel
    • 1
    • 3
  • Matthias O. Franz
    • 2
  • Peter Stilz
    • 3
  • Hans-Ulrich Schnitzler
    • 3
  1. 1.Department of NeurobiologyWeizmann Institute of ScienceRehovotIsrael
  2. 2.Faculty of InformaticsUniversity of Applied SciencesConstanceGermany
  3. 3.Animal Physiology, Institute of NeurobiologyUniversity of TuebingenTuebingenGermany

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