Journal of Comparative Physiology A

, Volume 199, Issue 2, pp 159–168 | Cite as

Size does not matter: size-invariant echo-acoustic object classification

  • Daria Genzel
  • Lutz Wiegrebe
Original Paper


Echolocating bats can not only extract spatial information from the auditory analysis of their ultrasonic emissions, they can also discriminate, classify and identify the three-dimensional shape of objects reflecting their emissions. Effective object recognition requires the segregation of size and shape information. Previous studies have shown that, like in visual object recognition, bats can transfer an echo-acoustic object discrimination task to objects of different size and that they spontaneously classify scaled versions of virtual echo-acoustic objects according to trained virtual-object standards. The current study aims to bridge the gap between these previous findings using a different class of real objects and a classification—instead of a discrimination paradigm. Echolocating bats (Phyllostomus discolor) were trained to classify an object as either a sphere or an hour-glass shaped object. The bats spontaneously generalised this classification to objects of the same shape. The generalisation cannot be explained based on similarities of the power spectra or temporal structures of the echo-acoustic object images and thus require dedicated neural mechanisms dealing with size-invariant echo-acoustic object analysis. Control experiments with human listeners classifying the echo-acoustic images of the objects confirm the universal validity of auditory size invariance. The current data thus corroborate and extend previous psychophysical evidence for sonar auditory-object normalisation and suggest that the underlying auditory mechanisms following the initial neural extraction of the echo-acoustic images in echolocating bats may be very similar in bats and humans.


Echolocation Object classification Size-invariance Human vowels Normalisation 





Two-alternative, forced-choice


Light-emitting diode


Impulse response



This work was funded by a grant from the ‘Volkswagenstiftung’ (I/79 780 and I/83 838 to Lutz Wiegrebe). We would also like to thank two anonymous reviewers for their constructive comments on an earlier version of the manuscript. The experiments are non-invasive and do not require an experimental license. Permission to keep and breed the animals was issued from the Regierung von Oberbayern (5.1-568-Ste, Aktenzeichen der Haltungsgenehmigung).


  1. Alves-Pinto A, Lopez-Poveda EA (2005) Detection of high-frequency spectral notches as a function of level. J Acoust Soc Am 118:2458–2469PubMedCrossRefGoogle Scholar
  2. Aubauer R, Au WWL (1998) Phantom echo generation: a new technique for investigating dolphin echolocation. J Acoust Soc Am 104:1165–1170PubMedCrossRefGoogle Scholar
  3. Falk B, Williams T, Aytekin M, Moss CF (2011) Adaptive behavior for texture discrimination by the free-flying big brown bat, Eptesicus fuscus. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 197:491–503PubMedCrossRefGoogle Scholar
  4. Firzlaff U, Schuchmann M, Grunwald JE, Schuller G, Wiegrebe L (2007) Object-oriented echo perception and cortical representation in echolocating bats. PLoS Biol 5:e100PubMedCrossRefGoogle Scholar
  5. Fiser J, Biederman I (1995) Size invariance in visual object priming of gray-scale images. Perception 24:741–748PubMedCrossRefGoogle Scholar
  6. Furmanski CS, Engel SA (2000) Perceptual learning in object recognition: object specificity and size Invariance. Vision Res 40:473–484PubMedCrossRefGoogle Scholar
  7. Genzel D, Wiegrebe L (2008) Time-variant spectral peak and notch detection in echolocation-call sequences in bats. J Exp Biol 211:9–14PubMedCrossRefGoogle Scholar
  8. Goerlitz HR, Hubner M, Wiegrebe L (2008) Comparing passive and active hearing: spectral analysis of transient sounds in bats. J Exp Biol 211:1850–1858PubMedCrossRefGoogle Scholar
  9. Green DM (1996) Discrimination changes in spectral shape: profile analysis. Acustica 82:S31–S36Google Scholar
  10. Griffiths TD, Warren JD (2004) What is an auditory object? Nat Rev Neurosci 5:887–892PubMedCrossRefGoogle Scholar
  11. Grunwald JE, Schornich S, Wiegrebe L (2004) Classification of natural textures in echolocation. Proc Natl Acad Sci USA 101:5670–5674PubMedCrossRefGoogle Scholar
  12. Houben MMJ, Kohlrausch A, Hermes DJ (2004) Perception of the size and speed of rolling balls by sound. Speech Commun 43:331–345CrossRefGoogle Scholar
  13. Houben MMJ, Kohlrausch A, Hermes DJ (2005) The contribution of spectral and temporal information to the auditory perception of the size and speed of rolling balls. Acta Acustica United Acustica 91:1007–1015Google Scholar
  14. Irino T, Patterson RD (2002) Segregating information about the size and shape of the vocal tract using a time-domain auditory model: the stabilised wavelet-mellin transform. Speech Commun 36:181–203CrossRefGoogle Scholar
  15. Ives DT, Smith DR, Patterson RD (2005) Discrimination of speaker size from syllable phrases. J Acoust Soc Am 118:3816–3822PubMedCrossRefGoogle Scholar
  16. Krumbholz K, Schmidt S (1999) Perception of complex tones and its analogy to echo spectral analysis in the bat, Megaderma lyra. J Acoust Soc Am 105:898–911PubMedCrossRefGoogle Scholar
  17. Larsby B, Arlinger S (1998) A method for evaluating temporal, spectral and combined temporal-spectral resolution of hearing. Scand Audiol 27:3–12PubMedCrossRefGoogle Scholar
  18. Larsen A, Bundesen C (1978) Size scaling in visual pattern recognition. J Exp Psychol Hum Percept Perform 4:1–20PubMedCrossRefGoogle Scholar
  19. Lloyd-Jones TJ, Luckhurst L (2002) Effects of plane rotation, task, and complexity on recognition of familiar and chimeric objects. Mem Cognit 30:499–510PubMedCrossRefGoogle Scholar
  20. Logothetis NK, Sheinberg DL (1996) Visual object recognition. Annu Rev Neurosci 19:577–621PubMedCrossRefGoogle Scholar
  21. Macpherson EA, Middlebrooks JC (2003) Vertical-plane sound localization probed with ripple-spectrum noise. J Acoust Soc Am 114:430–445PubMedCrossRefGoogle Scholar
  22. Nowak RM (1994) Walker’s Bats of the World. Johns Hopkins University Press, LondonGoogle Scholar
  23. Preisler A, Schmidt S (1998) Spontaneous classification of complex tones at high and ultrasonic frequencies in the bat, Megaderma lyra. J Acoust Soc Am 103:2595–2607PubMedCrossRefGoogle Scholar
  24. Sams M, Salmelin R (1994) Evidence of Sharp Frequency Tuning in the Human Auditory-Cortex. Hear Res 75:67–74PubMedCrossRefGoogle Scholar
  25. Sawamura H, Georgieva S, Vogels R, Vanduffel W, Orban GA (2005) Using functional magnetic resonance imaging to assess adaptation and size invariance of shape processing by humans and monkeys. J Neurosci 25:4294–4306PubMedCrossRefGoogle Scholar
  26. Schebesch G, Lingner A, Firzlaff U, Wiegrebe L, Grothe B (2010) Perception and neural representation of size-variant human vowels in the Mongolian gerbil (Meriones unguiculatus). Hear Res 261:1–8PubMedCrossRefGoogle Scholar
  27. Schmidt S (1988) Evidence for a spectral basis of texture perception in bat sonar. Nature 331:617–619PubMedCrossRefGoogle Scholar
  28. Schmidt S (1992) Perception of structured phantom targets in the echolocating bat, Megaderma lyra. J Acoust Soc Am 91:2203–2223PubMedCrossRefGoogle Scholar
  29. Schörnich S, Wiegrebe L (2008) Phase sensitivity in bat sonar revisited. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 194(1):61–67Google Scholar
  30. Simmons JA (2012) Bats use a neuronally implemented computational acoustic model to form sonar images. Curr Opin Neurobiol 22:311–319PubMedCrossRefGoogle Scholar
  31. Simon R, Holderied MW, von Helversen O (2006) Size discrimination of hollow hemispheres by echolocation in a nectar feeding bat. J Exp Biol 209:3599–3609PubMedCrossRefGoogle Scholar
  32. Smith DR, Patterson RD (2005) The interaction of glottal-pulse rate and vocal-tract length in judgements of speaker size, sex, and age. J Acoust Soc Am 118:3177–3186PubMedCrossRefGoogle Scholar
  33. Smith DR, Patterson RD, Turner R, Kawahara H, Irino T (2005) The processing and perception of size information in speech sounds. J Acoust Soc Am 117:305–318PubMedCrossRefGoogle Scholar
  34. van Dinther R, Patterson RD (2006) Perception of acoustic scale and size in musical instrument sounds. J Acoust Soc Am 120:2158–2176PubMedCrossRefGoogle Scholar
  35. von der Emde G (2004) Distance and shape: perception of the 3-dimensional world by weakly electric fish. J Physiol Paris 98:67–80PubMedCrossRefGoogle Scholar
  36. von Helversen D (2004) Object classification by echolocation in nectar feeding bats: size-independent generalization of shape. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 190:515–521Google Scholar
  37. von Helversen D, von Helversen O (1999) Acoustic guide in bat-pollinated flower. Nature 398:759–760CrossRefGoogle Scholar
  38. Warren JD, Jennings AR, Griffiths TD (2005) Analysis of the spectral envelope of sounds by the human brain. Neuroimage 24:1052–1057PubMedCrossRefGoogle Scholar
  39. Weissenbacher P, Wiegrebe L (2003) Classification of virtual objects in the echolocating bat, Megaderma lyra. Behav Neurosci 117:833–839PubMedCrossRefGoogle Scholar
  40. Wiegrebe L (2008) An autocorrelation model of bat sonar. Biol Cybern 98:587–595PubMedCrossRefGoogle Scholar
  41. Wiegrebe L, Schmidt S (1996) Temporal integration in the echolocating bat, Megaderma lyra. Hear Res 102:35–42PubMedCrossRefGoogle Scholar
  42. Wittekindt A, Drexl M, Kossl M (2005) Cochlear sensitivity in the lesser spear-nosed bat, Phyllostomus discolor. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 191:31–36PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Division of Neurobiology, Department Biology IILudwig-Maximilians-Universitaet MunichMartinsried-PlaneggGermany

Personalised recommendations