Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Performance variability enables adaptive plasticity of ‘crystallized’ adult birdsong

Nature volume 450, pages 1240–1244 (2007)Cite this article

Abstract

Significant trial-by-trial variation persists even in the most practiced skills. One prevalent view is that such variation is simply ‘noise’ that the nervous system is unable to control or that remains below threshold for behavioural relevance1,2,3. An alternative hypothesis is that such variation enables trial-and-error learning, in which the motor system generates variation and differentially retains behaviours that give rise to better outcomes. Here we test the latter possibility for adult bengalese finch song. Adult birdsong is a complex, learned motor skill that is produced in a highly stereotyped fashion from one rendition to the next4,5. Nevertheless, there is subtle trial-by-trial variation even in stable, ‘crystallized’ adult song6,7,8. We used a computerized system to monitor small natural variations in the pitch of targeted song elements and deliver real-time auditory disruption to a subset of those variations. Birds rapidly shifted the pitch of their vocalizations in an adaptive fashion to avoid disruption. These vocal changes were precisely restricted to the targeted features of song. Hence, birds were able to learn effectively by associating small variations in their vocal behaviour with differential outcomes. Such a process could help to maintain stable, learned song despite changes to the vocal control system arising from ageing or injury. More generally, our results suggest that residual variability in well learned skills is not entirely noise but rather reflects meaningful motor exploration that can support continuous learning and optimization of performance.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Differential reinforcement can adaptively alter features of adult song.
Figure 2: Adaptive shifts in fundamental frequency occur rapidly and recover.
Figure 3: Changes are restricted to targeted features of song.
Figure 4: Delayed feedback prevents adaptive pitch shifts.
Figure 5: Incremental adjustment of threshold drives large pitch changes.

Similar content being viewed by others

References

  1. Beers, R. J. V., Baraduc, P. & Wolpert, D. M. Role of uncertainty in sensorimotor control. Phil. Trans. R. Soc. Lond. B 357, 1137–1145 (2002)

    Article  Google Scholar 

  2. Todorov, E. Optimality principles in sensorimotor control. Nature Neurosci. 7, 907–915 (2004)

    Article  CAS  Google Scholar 

  3. Harris, C. M. & Wolpert, D. M. Signal-dependent noise determines motor planning. Nature 394, 780–784 (1998)

    Article  ADS  CAS  Google Scholar 

  4. Konishi, M. Birdsong: From behavior to neuron. Annu. Rev. Neurosci. 8, 125–170 (1985)

    Article  CAS  Google Scholar 

  5. Deregnaucourt, S. et al. How sleep affects the developmental learning of bird song. Nature 433, 710–716 (2005)

    Article  ADS  CAS  Google Scholar 

  6. Sossinka, R. & Bohner, J. Song types in the zebra finch Poephila guttata castanotis. Z. Tierpsychol. 53, 123–132 (1980)

    Article  Google Scholar 

  7. Kao, M. H., Doupe, A. J. & Brainard, M. S. Contributions of an avian basal ganglia-forebrain circuit to real-time modulation of song. Nature 433, 638–643 (2005)

    Article  ADS  CAS  Google Scholar 

  8. Kao, M. H. & Brainard, M. S. Lesions of an avian basal ganglia circuit prevent context-dependent changes to song variability. J. Neurophysiol. 96, 1441–1455 (2006)

    Article  Google Scholar 

  9. Doupe, A. J. & Kuhl, P. K. Birdsong and human speech: common themes and mechanisms. Annu. Rev. Neurosci. 22, 567–631 (1999)

    Article  CAS  Google Scholar 

  10. Nordeen, K. W. & Nordeen, E. J. Auditory feedback is necessary for the maintenance of stereotyped song in adult zebra finches. Behav. Neural Biol. 57, 58–66 (1992)

    Article  CAS  Google Scholar 

  11. Okanoya, K. & Yamaguchi, A. Adult Bengalese finches (Lonchura striata var. domestica) require real-time auditory feedback to produce normal song syntax. J. Neurobiol. 33, 343–356 (1997)

    Article  CAS  Google Scholar 

  12. Woolley, S. M. & Rubel, E. W. Bengalese finches Lonchura Striata domestica depend upon auditory feedback for the maintenance of adult song. J. Neurosci. 17, 6380–6390 (1997)

    Article  CAS  Google Scholar 

  13. Leonardo, A. & Konishi, M. Decrystallization of adult birdsong by perturbation of auditory feedback. Nature 399, 466–470 (1999)

    Article  ADS  CAS  Google Scholar 

  14. Zevin, J. D., Seidenberg, M. S. & Bottjer, S. W. Limits on reacquisition of song in adult zebra finches exposed to white noise. J. Neurosci. 24, 5849–5862 (2004)

    Article  CAS  Google Scholar 

  15. Sutton, R. S. & Barto, A. G. Reinforcement Learning: An Introduction (MIT Press, Cambridge, Massachusetts, 1998)

    MATH  Google Scholar 

  16. Doya, K. & Sejnowski, T. in The New Cognitive Neurosciences (ed. Gazzaniga, M.) 469–482 (MIT Press, Cambridge, Massachusetts, 2000)

    Google Scholar 

  17. Troyer, T. & Doupe, A. J. An associational model of birdsong sensorimotor learning. I. Efference copy and the learning of song syllables. J. Neurophys. 84, 1204–1223 (2000)

    Article  CAS  Google Scholar 

  18. Fiete, I. R., Fee, M. S. & Seung, H. S. Model of birdsong learning based on gradient estimation by dynamic perturbation of neural conductances. J. Neurophys. 98, 2038–2057 (2007)

    Article  Google Scholar 

  19. Olveczky, B. P., Andalman, A. S. & Fee, M. S. Vocal experimentation in the juvenile songbird requires a basal ganglia circuit. PLoS Biol. 3, e153 (2005)

    Article  Google Scholar 

  20. Hessler, N. A. & Doupe, A. J. Social context modulates singing-related neural activity in the songbird forebrain. Nature Neurosci. 2, 209–211 (1999)

    Article  CAS  Google Scholar 

  21. Bottjer, S. W., Miesner, E. A. & Arnold, A. P. Forebrain lesions disrupt development but not maintenance of song in passerine birds. Science 224, 901–903 (1984)

    Article  ADS  CAS  Google Scholar 

  22. Scharff, C. & Nottebohm, F. A comparative study of the behavioral deficits following lesions of various parts of the zebra finch song system: implications for vocal learning. J. Neurosci. 11, 2896–2913 (1991)

    Article  CAS  Google Scholar 

  23. Amir, O., Amir, N. & Kishon-Rabin, L. The effect of superior auditory skills on vocal accuracy. J. Acoust. Soc. Am. 113, 1102–1108 (2003)

    Article  ADS  Google Scholar 

  24. Sundberg, J., Prame, E. & Iwarsson, J. in Vocal Fold Physiology, Controlling Complexity and Chaos (eds Davis, P. & Fletcher, N.) 291–306 (Singular Publishing Group, San Diego, 1996)

    Google Scholar 

  25. Dent, M. L., Dooling, R. J. & Pierce, A. S. Frequency discrimination in budgerigars (Melopsittacus undulatus): Effects of tone duration and tonal context. J. Acoust. Soc. Am. 107, 2657–2664 (2000)

    Article  ADS  CAS  Google Scholar 

  26. Fiete, I. R., Hahnloser, R. H., Fee, M. S. & Seung, H. S. Temporal sparseness of the premotor drive is important for rapid learning in a neural network model of birdsong. J. Neurophysiol. 92, 2274–2282 (2004)

    Article  Google Scholar 

  27. Sakata, J. T. & Brainard, M. S. Real-time contributions of auditory feedback to avian vocal motor control. J. Neurosci. 26, 9619–9628 (2006)

    Article  CAS  Google Scholar 

  28. Held, R., Efstathiou, A. & Greene, M. Adaptation to displaced and delayed visual feedback from the hand. J. Exp. Psychol. 72, 887–891 (1966)

    Article  Google Scholar 

  29. Churchland, M. M., Afshar, A. & Shenoy, K. V. A central source of movement variability. Neuron 52, 1085–1096 (2006)

    Article  CAS  Google Scholar 

  30. Churchland, M. M., Santhanam, G. & Shenoy, K. V. Preparatory activity in premotor and motor cortex reflects the speed of the upcoming reach. J. Neurophysiol. 96, 3130–3146 (2006)

    Article  Google Scholar 

  31. Leonardo, A. Experimental test of the birdsong error-correction model. Proc. Natl Acad. Sci. USA 101, 16935–16940 (2004)

    Article  ADS  CAS  Google Scholar 

  32. Kozhevnikov, A. & Fee, M. S. Singing-related activity of identified HVC neurons in the zebra finch. J. Neurophysiol. 97, 4271–4283 (2007)

    Article  Google Scholar 

Download references

Acknowledgements

We thank A. Doupe, L. Frank, T. Warren, M. Wohlgemuth, S. Sober, J. Sakata, C. Hampton and J. Wong for comments. This work was supported by an NIDCD NRSA postdoctoral fellowship and the Sloan-Swartz Foundation (E.C.T.) and by an NIDCD R01 award, an NIMH Conte Center for Neuroscience Research award and a McKnight Foundation Scholars Award (M.S.B).

Author Contributions E.C.T. performed the experiments and analysis; E.C.T. and M.S.B. designed the experiments and wrote the manuscript.

Author information

Authors and Affiliations

  1. Department of Physiology, Keck Center for Integrative Neuroscience, Sloan-Swartz Center for Theoretical Neurobiology, University of California, San Francisco, California 94143-0444, USA,

    Evren C. Tumer & Michael S. Brainard

  2. Department of Psychiatry, University of California, San Francisco, California 94143, USA,

    Michael S. Brainard

Authors
  1. Evren C. Tumer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael S. Brainard
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Evren C. Tumer.

Supplementary information

Supplementary Information

This file contains Supplementary Notes with Supplementary Figures S1-S3 showing: details of differential reinforcement; relationship between baseline variation and capacity for adaptive change and how non-contingent feedback did not alter song. (PDF 254 kb)

Supplementary Audio 1

This file contains Supplementary Audio 1 demonstrating the stereotypy of normal adult Bengalese finch song. Three separate songs are played corresponding to the spectrograms of Figure 1a. (WAV 310 kb)

Supplementary Video 1

This file contains Supplementary Video 1 demonstrating the salience of changes driven by progressively increasing the reinforcement threshold. Points and sounds reflect pitch of 20 randomly selected syllables from each of 2 days of baseline data and 13 days of differential reinforcement. Blue line indicates reinforcement threshold. Data from experiment of Figure 5a. (MOV 454 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Tumer, E., Brainard, M. Performance variability enables adaptive plasticity of ‘crystallized’ adult birdsong. Nature 450, 1240–1244 (2007). https://doi.org/10.1038/nature06390

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature06390

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing