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The role of nonlinear dynamics of the syrinx in the vocalizations of a songbird

Author

Listed:
  • Michale S. Fee

    (Bell Laboratories, Lucent Technologies)

  • Boris Shraiman

    (Bell Laboratories, Lucent Technologies)

  • Bijan Pesaran

    (California Institute of Technology)

  • Partha P. Mitra

    (Bell Laboratories, Lucent Technologies)

Abstract

Birdsong is characterized by the modulation of sound properties over a wide range of timescales1. Understanding the mechanisms by which the brain organizes this complex temporal behaviour is a central motivation in the study of the song control and learning system2,3,4,5,6,7,8. Here we present evidence that, in addition to central neural control, a further level of temporal organization is provided by nonlinear oscillatory dynamics that are intrinsic to the avian vocal organ. A detailed temporal and spectral examination of song of the zebra finch (Taeniopygia guttata) reveals a class of rapid song modulations that are consistent with transitions in the dynamical state of the syrinx. Furthermore, in vitro experiments show that the syrinx can produce a sequence of oscillatory states that are both spectrally and temporally complex in response to the slow variation of respiratory or syringeal parameters. As a consequence, simple variations in a small number of neural signals can result in a complex acoustic sequence.

Suggested Citation

  • Michale S. Fee & Boris Shraiman & Bijan Pesaran & Partha P. Mitra, 1998. "The role of nonlinear dynamics of the syrinx in the vocalizations of a songbird," Nature, Nature, vol. 395(6697), pages 67-71, September.
  • Handle: RePEc:nat:nature:v:395:y:1998:i:6697:d:10.1038_25725
    DOI: 10.1038/25725
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    Cited by:

    1. Timothy E Holy & Zhongsheng Guo, 2005. "Ultrasonic Songs of Male Mice," PLOS Biology, Public Library of Science, vol. 3(12), pages 1-1, November.
    2. Avishek Paul & Helen McLendon & Veronica Rally & Jon T Sakata & Sarah C Woolley, 2021. "Behavioral discrimination and time-series phenotyping of birdsong performance," PLOS Computational Biology, Public Library of Science, vol. 17(4), pages 1-21, April.

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