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.

  • Science and Society
  • Published:

Music training for the development of auditory skills

Abstract

The effects of music training in relation to brain plasticity have caused excitement, evident from the popularity of books on this topic among scientists and the general public. Neuroscience research has shown that music training leads to changes throughout the auditory system that prime musicians for listening challenges beyond music processing. This effect of music training suggests that, akin to physical exercise and its impact on body fitness, music is a resource that tones the brain for auditory fitness. Therefore, the role of music in shaping individual development deserves consideration.

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

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Figure 1: Neural representation of pitch, timing and timbre in the human auditory brainstem.
Figure 2: Transfer effect and selective enhancement in musicians.

References

  1. Zatorre, R. J., Chen, J. L. & Penhune, V. B. When the brain plays music: auditory–motor interactions in music perception and production. Nature Rev. Neurosci. 8, 547–558 (2007).

    Article  CAS  Google Scholar 

  2. Kraus, N., Skoe, E., Parbery-Clark, A. & Ashley, R. Experience-induced malleability in neural encoding of pitch, timbre, and timing. Ann. NY Acad. Sci. 1169, 543–557 (2009).

    Article  Google Scholar 

  3. Habib, M. & Besson, M. What do music training and musical experience teach us about brain plasticity? Music Percept. 26, 279–285 (2009).

    Article  Google Scholar 

  4. Zatorre, R. & McGill, J. Music, the food of neuroscience? Nature 434, 312–315 (2005).

    Article  CAS  Google Scholar 

  5. Peretz, I. & Zatorre, R. J. Brain organization for music processing. Annu. Rev. Psychol. 56, 89–114 (2005).

    Article  Google Scholar 

  6. Hannon, E. E. & Trainor, L. J. Music acquisition: effects of enculturation and formal training on development. Trends Cogn. Sci. 11, 466–472 (2007).

    Article  Google Scholar 

  7. Pantev, C. et al. Increased auditory cortical representation in musicians. Nature 392, 811–814 (1998).

    Article  CAS  Google Scholar 

  8. Gaser, C. & Schlaug, G. Brain structures differ between musicians and non-musicians. J. Neurosci. 23, 9240–9245 (2003).

    Article  CAS  Google Scholar 

  9. Schneider, P. et al. Morphology of Heschl's gyrus reflects enhanced activation in the auditory cortexof musicians. Nature Neurosci. 5, 688–694 (2002).

    Article  CAS  Google Scholar 

  10. Fujioka, T., Trainor, L. J., Ross, B., Kakigi, R. & Pantev, C. Musical training enhances automatic encoding of melodic contour and interval structure. J. Cogn. Neurosci. 16, 1010–1021 (2004).

    Article  Google Scholar 

  11. Lee, K. M., Skoe, E., Kraus, N. & Ashley, R. Selective subcortical enhancement of musical intervals in musicians. J. Neurosci. 29, 5832–5840 (2009).

    Article  CAS  Google Scholar 

  12. Hyde, K. L. et al. Musical training shapes structural brain development. J. Neurosci. 29, 3019–3025 (2009).

    Article  CAS  Google Scholar 

  13. Moreno, S. et al. Musical training influences linguistic abilities in 8-year-old children: more evidence for brain plasticity. Cereb. Cortex 19, 712–723 (2009).

    Article  Google Scholar 

  14. Münte, T. F., Altenmüller, E. & Jäncke, L. The musician's brain as a model of neuroplasticity. Nature Rev. Neurosci. 3, 473–478 (2002).

    Article  Google Scholar 

  15. Forgeard, M., Winner, E., Norton, A. & Schlaug, G. Practicing a musical instrument in childhood is associated with enhanced verbal ability and nonverbal reasoning. PLoS ONE 3, e3566 (2008).

    Article  Google Scholar 

  16. Magne, C., Schon, D. & Besson, M. Musician children detect pitch violations in both music and language better than nonmusician children: behavioral and electrophysiological approaches. J. Cogn. Neurosci. 18, 199–211 (2006).

    Article  Google Scholar 

  17. Parbery-Clark, A., Skoe, E. & Kraus, N. Musical experience limits the degradative effects of background noise on the neural processing of sound. J. Neurosci. 29, 14100–14107 (2009).

    Article  CAS  Google Scholar 

  18. Wong, P. C., Skoe, E., Russo, N. M., Dees, T. & Kraus, N. Musical experience shapes human brainstem encoding of linguistic pitch patterns. Nature Neurosci. 10, 420–422 (2007).

    Article  CAS  Google Scholar 

  19. Patel, A. D. Language, music, syntax and the brain. Nature Neurosci. 6, 674–681 (2003).

    Article  CAS  Google Scholar 

  20. Tzounopoulos, T. & Kraus, N. Learning to encode timing: mechanisms of plasticity in the auditory brainstem. Neuron 62, 463–469 (2009).

    Article  CAS  Google Scholar 

  21. Besson, M., Schon, D., Moreno, S., Santos, A. & Magne, C. Influence of musical expertise and musical training on pitch processing in music and language. Restor. Neurol. Neurosci. 25, 399–410 (2007).

    PubMed  Google Scholar 

  22. Musacchia, G., Sams, M., Skoe, E. & Kraus, N. Musicians have enhanced subcortical auditory and audiovisual processing of speech and music. Proc. Natl Acad. Sci. USA 104, 15894–15898 (2007).

    Article  CAS  Google Scholar 

  23. Belin, P. Voice processing in human and non-human primates. Phil. Trans. R. Soc. Lond. B 361, 2091–2107 (2006).

    Article  Google Scholar 

  24. Chandrasekaran, B. & Kraus, N. The scalp-recorded brainstem response to speech: neural origins and plasticity. Psychophysiology 47, 236–246 (2010).

    Article  Google Scholar 

  25. Wong, P. C. M. & Perrachione, T. K. Learning pitch patterns in lexical identification by native English-speaking adults. Appl. Psycholinguist. 28, 565–585 (2007).

    Article  Google Scholar 

  26. Song, J. H., Skoe, E., Wong, P. C. & Kraus, N. Plasticity in the adult human auditory brainstem following short-term linguistic training. J. Cogn. Neurosci. 20, 1892–1902 (2008).

    Article  Google Scholar 

  27. Krishnan, A., Xu, Y.S., Gandour, J. & Cariani, P. Encoding of pitch in the human brainstem is sensitive to language experience. Cogn. Brain Res. 25, 161–168 (2005).

    Article  Google Scholar 

  28. Skoe, E. & Kraus, N. Auditory brain stem response to complex sounds: a tutorial. Ear Hear. 31, 302–324.

  29. Galbraith, G. C., Arbagey, P. W., Branski, R., Comerci, N. & Rector, P. M. Intelligible speech encoded in the human brain stem frequency-following response. Neuroreport 6, 2363–2367 (1995).

    Article  CAS  Google Scholar 

  30. Suga, N. Role of corticofugal feedback in hearing. J. Comp. Physiol. A, Neuroethol. Sens. Neural. Behav. Physiol. 194, 169–183 (2008).

    Article  Google Scholar 

  31. Suga, N. & Ma, X. Multiparametric corticofugal modulation and plasticity in the auditory system. Nature Rev. Neurosci. 4, 783–794 (2003).

    Article  CAS  Google Scholar 

  32. Strait, D. L., Kraus, N., Skoe, E. & Ashley, R. Musical experience and neural efficiency: effects of training on subcortical processing of vocal expressions of emotion. Eur. J. Neurosci. 29, 661–668 (2009).

    Article  Google Scholar 

  33. Bidelman, G. M., Gandour, J. T. & Krishnan, A. Cross-domain effects of music and language experience on the representation of pitch in the human auditory brainstem. J. Cogn. Neurosci. 19 Nov 2009 (doi:10.1162/jocn.2009.21362).

    Article  Google Scholar 

  34. Chartrand, J. P. & Belin, P. Superior voice timbre processing in musicians. Neurosci. Lett. 405, 164–167 (2006).

    Article  CAS  Google Scholar 

  35. Schellenberg, E. G. Music lessons enhance IQ. Psychol. Sci. 15, 511–514 (2004).

    Article  Google Scholar 

  36. Schellenberg, E. G. in The Child as Musician: A Handbook of Musical Development (ed. McPherson, G. E. E.) 111–134 (Oxford Univ. Press, Oxford, UK, 2006).

    Book  Google Scholar 

  37. Schellenberg, E. G. & Peretz, I. Music, language and cognition: unresolved issues. Trends Cogn. Sci. 12, 45–46 (2008).

    Article  Google Scholar 

  38. Strait, D., Kraus, N., Parbery-Clark, A. & Ashley, R. Musical experience shapes top-down auditory mechanisms: evidence from masking and auditory attention performance. Hear. Res. 261, 22–29 (2010).

    Article  Google Scholar 

  39. Strait, D. L., Kraus, N., Skoe, E. & Ashley, R. Musical experience promotes subcortical efficiency in processing emotional vocal sounds. Ann. NY Acad. Sci. 1169, 209–213 (2009).

    Article  Google Scholar 

  40. Fujioka, T., Trainor, L. J., Ross, B., Kakigi, R. & Pantev, C. Automatic encoding of polyphonic melodies in musicians and nonmusicians. J. Cogn. Neurosci. 17, 1578–1592 (2005).

    Article  Google Scholar 

  41. Chan, A. S., Ho, Y. C. & Cheung, M. C. Music training improves verbal memory. Nature 396, 128 (1998).

    Article  CAS  Google Scholar 

  42. Nager, W., Kohlmetz, C., Altenmüller, E., Rodriguez-Fornells, A. & Münte, T. F. The fate of sounds in conductors' brains: an ERP study. Brain Res. Cogn. Brain Res. 17, 83–93 (2003).

    Article  Google Scholar 

  43. Seppänen, M., Brattico, E. & Tervaniemi, M. Practice strategies of musicians modulate neural processing and the learning of sound-patterns. Neurobiol. Learn. Mem. 87, 236–247 (2007).

    Article  Google Scholar 

  44. Winkler, I., Denham, S. L. & Nelken, I. Modeling the auditory scene: predictive regularity representations and perceptual objects. Trends Cogn. Sci. 13, 532–540 (2009).

    Article  Google Scholar 

  45. Saffran, J. R., Aslin, R. N. & Newport, E. L. Statistical learning by 8-month-old infants. Science 274, 1926–1928 (1996).

    Article  CAS  Google Scholar 

  46. Luo, F., Wang, Q., Kashani, A. & Yan, J. Corticofugal modulation of initial sound processing in the brain. J. Neurosci. 28, 11615–11621 (2008).

    Article  CAS  Google Scholar 

  47. Trainor, L. J. & Zatorre, R. in Oxford Handbook of Music Psychology (eds Hallen, S., Cross, I. & Thaut, M.) 171–182 (Oxford Univ. Press, Oxford, UK, 2009).

    Google Scholar 

  48. Suga, N., Xiao, Z., Ma, X. & Ji, W. Plasticity and corticofugal modulation for hearing in adult animals. Neuron 36, 9–18 (2002).

    Article  CAS  Google Scholar 

  49. Koelsch, S., Schroger, E. & Tervaniemi, M. Superior pre-attentive auditory processing in musicians. Neuroreport 10, 1309–1313 (1999).

    Article  CAS  Google Scholar 

  50. van Zuijen, T. L., Sussman, E., Winkler, I., Naatanen, R. & Tervaniemi, M. Auditory organization of sound sequences by a temporal or numerical regularity — a mismatch negativity study comparing musicians and non-musicians. Brain Res. Cogn. Brain Res. 23, 270–276 (2005).

    Article  Google Scholar 

  51. Brashears, S. M., Morlet, T. G., Berlin, C. I. & Hood, L. J. Olivocochlear efferent suppression in classical musicians. J. Am. Acad. Audiol. 14, 314–324 (2003).

    PubMed  Google Scholar 

  52. Perrot, X., Micheyl, C. & Khalfa, S. Stronger bilateral efferent influences on cochlear biomechanical activity in musicians than in non-musicians. Neurosci. Lett. 262, 167–170 (1999).

    Article  CAS  Google Scholar 

  53. Fitch, W. T. The biology and evolution of music: a comparative perspective. Cognition 100, 173–215 (2006).

    Article  Google Scholar 

  54. Patel, A. D. in Emerging Disciplines (ed. Bailar, M.) 91–144 (Rice Univ. Press, Houston, 2010).

    Google Scholar 

  55. Pinker, S. How the Mind Works (Allen Lane, London, 1997).

    Google Scholar 

  56. Chandrasekaran, B., Hornickel, J. M., Skoe, E., Nicol, T. & Kraus, N. Context-dependent encoding in the human auditory brainstem relates to hearing speech in noise: implications for developmental dyslexia. Neuron 64, 311–319 (2009).

    Article  CAS  Google Scholar 

  57. Wong, P. C., Perrachione, T. K. & Parrish, T. B. Neural characteristics of successful and less successful speech and word learning in adults. Hum. Brain Mapp. 28, 995–1006 (2007).

    Article  Google Scholar 

  58. Wong, P. C. et al. Volume of left Heschl's Gyrus and linguistic pitch learning. Cereb. Cortex 18, 828–836 (2008).

    Article  Google Scholar 

  59. Overy, K. From timing deficits to musical intervention. Ann. NY Acad. Sci. 999, 497–505 (2003).

    Article  Google Scholar 

  60. Tallal, P. & Gaab, N. Dynamic auditory processing, musical experience and language development. Trends Cogn. Sci. 29, 382–390 (2006).

    CAS  Google Scholar 

  61. Tallal, P. Auditory temporal perception, phonics, and reading disabilities in children. Brain Lang. 9, 182–198 (1980).

    Article  CAS  Google Scholar 

  62. Chandrasekaran, B. & Kraus, N. Music, noise-exclusion, and learning. Music Percept. 27, 297–306 (2010).

    Article  Google Scholar 

  63. Hornickel, J., Skoe, E., Nicol, T., Zecker, S. & Kraus, N. Subcortical differentiation of stop consonants relates to reading and speech-in-noise perception. Proc. Natl Acad. Sci. USA 106, 13022–13027 (2009).

    Article  CAS  Google Scholar 

  64. Parbery-Clark, A., Skoe, E., Lam, C. & Kraus, N. Musician enhancement for speech-in-noise. Ear Hear. 30, 653–661 (2009).

    Article  Google Scholar 

  65. Musacchia, G., Strait, D. & Kraus, N. Relationships between behavior, brainstem and cortical encoding of seen and heard speech in musicians and non-musicians. Hear. Res. 241, 34–42 (2008).

    Article  Google Scholar 

  66. Trainor, L. J. Are there critical periods for musical development? Dev. Psychobiol. 46, 262–278 (2005).

    Article  Google Scholar 

  67. Watanabe, D., Savion-Lemieux, T. & Penhune, V. The effect of early musical training on adult motor performance: evidence for a sensitive period in motor learning. Exp. Brain Res. 176, 332–340 (2007).

    Article  Google Scholar 

  68. Kratus, J. Music education at the tipping point. Music Educ. J. 94, 42 (2007).

    Article  Google Scholar 

  69. Kinney, D. W. Selected demographic variables, school music participation, and achievement test scores of urban middle school students. J. Res. Music Educ. 56, 145–161 (2008).

    Article  Google Scholar 

  70. Shield, B. M. & Dockrell, J. E. The effects of environmental and classroom noise on the academic attainments of primary school children. J. Acoust. Soc. Am. 123, 133–144 (2008).

    Article  Google Scholar 

  71. Sperling, A. J., Lu, Z. L., Manis, F. R. & Seidenberg, M. S. Deficits in perceptual noise exclusion in developmental dyslexia. Nature Neurosci. 8, 862–863 (2005).

    Article  CAS  Google Scholar 

  72. Ziegler, J. C., Pech-Georgel, C., George, F., Alario, F. X. & Lorenzi, C. Deficits in speech perception predict language learning impairment. Proc. Natl Acad. Sci. USA 102, 14110–14115 (2005).

    Article  CAS  Google Scholar 

  73. Ziegler, J. C., Pech-Georgel, C., George, F. & Lorenzi, C. Speech-perception-in-noise deficits in dyslexia. Dev. Sci. 12, 732–745 (2009).

    Article  Google Scholar 

  74. Banai, K. et al. Reading and subcortical auditory function. Cereb. Cortex 19, 2699–2707 (2009).

    Article  Google Scholar 

  75. Meltzoff, A. N., Kuhl, P. K., Movellan, J. & Sejnowski, T. J. Foundations for a new science of learning. Science 325, 284–288 (2009).

    Article  CAS  Google Scholar 

  76. Shahin, A. J., Roberts, L. E., Chau, W., Trainor, L. J. & Miller, L. M. Music training leads to the development of timbre-specific gamma band activity. Neuroimage 41, 113–122 (2008).

    Article  Google Scholar 

  77. Tervaniemi, M. Musicians — same or different? Ann. NY Acad. Sci. 1169, 151–156 (2009).

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported by the US National Science Foundation (grants SBE-0842376 and BCS-092275). We thank J. Song for her contribution towards the artwork and T. Nicol, D. Strait and K. Chan for their helpful comments on the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nina Kraus.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Related links

Related links

FURTHER INFORMATION

Kraus-Lab homepage

Glossary

Auditory stream segregation

The ability to piece together discrete perceptual events into streams.

Contour and interval information

Aspects of melodic information in music that are related to contour (upward or downward patterns of pitch changes) and interval (pitch distances between successive notes).

Frequency-following response

A neuronal ensemble response that phase-locks to the incoming stimulus.

Fundamental frequency

The lowest frequency of a voice, determined by the rate of vibration of the vocal folds. It generally corresponds to the voice's pitch.

Harmonic components in speech

Aspects of speech that depend on the rate of vibration of the vocal cords. A voice is composed of a fundamental tone and a series of higher frequencies that are called harmonics.

Magnetic source imaging

The detection of the changing magnetic fields that are associated with brain activity, and their subsequent overlaying onto magnetic resonance images to identify the precise source of the signal.

Mismatch negativity

A cortical event-related potential, measured using electroencephalography, that is elicited when a sequence of repeated stimuli (standards) is interrupted by an infrequent stimulus that deviates in sensory characteristics, such as intensity, frequency or duration.

Onset response

A neuronal ensemble response to the onset of sound.

Oto-acoustic emissions

Sounds that are generated in the inner ear, which can be recorded non-invasively. They serve as acoustic signatures of the cochlear biomechanical activity.

Pitch contours

Pitch changes that minimally contrast words in a tone language, such as Mandarin Chinese.

Time-varying components in speech

Dynamically changing acoustic events (for example, formant transitions) that correspond to articulatory changes during speech production.

Voice tagging

The ability to use voice pitch as a cue to 'tag' a familiar talker amid fluctuating background noise.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kraus, N., Chandrasekaran, B. Music training for the development of auditory skills. Nat Rev Neurosci 11, 599–605 (2010). https://doi.org/10.1038/nrn2882

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrn2882

This article is cited by

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