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Performance variability enables adaptive plasticity of ‘crystallized’ adult birdsong

Author

Listed:
  • Evren C. Tumer

    (Keck Center for Integrative Neuroscience, Sloan-Swartz Center for Theoretical Neurobiology, University of California, San Francisco, California 94143-0444, USA)

  • Michael S. Brainard

    (Keck Center for Integrative Neuroscience, Sloan-Swartz Center for Theoretical Neurobiology, University of California, San Francisco, California 94143-0444, USA
    University of California, San Francisco, California 94143, USA)

Abstract

The wrong stuff Why is it that even the best-trained athletes and musicians cannot perform perfectly? One thought is that residual variability in performance is 'noise' that reflects fundamental limits on our ability to control our movements. Experiments using the exceptionally well-rehearsed songs of adult songbirds as a model point to an alternative explanation. Computerized monitoring of the apparently stereotyped songs of adult Bengalese finches revealed minuscule variations in performance. When the birds were given corrections each time the song varied beyond a certain limit, they rapidly learned to adapt their vocalizations. The implication is that once learned, songs can be maintained despite subtle changes to the vocal system due to factors such as ageing. So behavioural 'noise', rather than simply being a nuisance, may reflect experimentation by the nervous system to refine performance.

Suggested Citation

  • Evren C. Tumer & Michael S. Brainard, 2007. "Performance variability enables adaptive plasticity of ‘crystallized’ adult birdsong," Nature, Nature, vol. 450(7173), pages 1240-1244, December.
    • Handle: RePEc:nat:nature:v:450:y:2007:i:7173:d:10.1038_nature06390
    DOI: 10.1038/nature06390
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    Cited by:

    1. Nina M van Mastrigt & Jeroen B J Smeets & Katinka van der Kooij, 2020. "Quantifying exploration in reward-based motor learning," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-14, April.
    2. Hanan Shteingart & Yonatan Loewenstein, 2014. "Reinforcement Learning and Human Behavior," Discussion Paper Series dp656, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    3. Sravani Kondapavulur & Stefan M. Lemke & David Darevsky & Ling Guo & Preeya Khanna & Karunesh Ganguly, 2022. "Transition from predictable to variable motor cortex and striatal ensemble patterning during behavioral exploration," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    4. Jonathan B Dingwell & Joby John & Joseph P Cusumano, 2010. "Do Humans Optimally Exploit Redundancy to Control Step Variability in Walking?," PLOS Computational Biology, Public Library of Science, vol. 6(7), pages 1-15, July.
    5. Simily Sabu & Arianna Curioni & Cordula Vesper & Natalie Sebanz & Günther Knoblich, 2020. "How does a partner’s motor variability affect joint action?," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-24, October.
    6. Julie E Miller & Austin T Hilliard & Stephanie A White, 2010. "Song Practice Promotes Acute Vocal Variability at a Key Stage of Sensorimotor Learning," PLOS ONE, Public Library of Science, vol. 5(1), pages 1-15, January.

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