Violinists Playing with and without Music Notation: Investigating Hemispheric Brainwave Activity

  • Valerie Ross
  • Zunairah Haji Murat
  • Norlida Buniyamin
  • Zaini Mohd-Zain
Part of the Studies in Computational Intelligence book series (SCI, volume 542)


Music has been known to improve learning and cognition. The ways in which musicians think and perform have increasingly become subjects of interest to scientists particularly in light of advances in neuroscience research. This study examines the brainwave activity of a group of violinists as they perform. Using electroencephalography (EEG), the left and right brainwaves of the musicians were recorded when they played a piece of music by first reading the score and then without reading the score. The results indicated that playing with music notation enhances left brain activity while playing without music notation enhances right brain activity. In addition, alpha brainwaves increased significantly on the right side of the brain when the violinist plays with and without score.


left brain activity right brain activity music-neuroscience violinists music learning strategies 


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  1. 1.
    Sarkamo, T., Tervaniemi, M., Laitinen, S., et al.: Music listening enhances cognitive recovery and mood after middle cerebra(ii) l artery stroke. Brain 131(pt. 3), 866–876 (2008)CrossRefGoogle Scholar
  2. 2.
    Gaser, C., Schlaug, G.: Brain structures differ between musicians and non musicians. J. Neurosci. 23(27), 9240–9245 (2003)Google Scholar
  3. 3.
    Hyde, K.L., Lerch, J., Norton, A., et al.: Musical training shapes strutural brain development. J. Neurosci. 29(10), 3019–3025 (2009)CrossRefGoogle Scholar
  4. 4.
    Janke, L.: The plastic human brain. Restor. Neurol. Neurosci. 27(5), 521–538 (2009)Google Scholar
  5. 5.
    ABRSM, Statistics of Examination Candidates, Associated Board of the Royal Schools of Music (2011), (retrieved August 20, 2011)
  6. 6.
    Ross, V.: External music examiners: micro-macro tasks in quality assurance. Journal of Music Education Research 11(4), 473–484 (2009)CrossRefGoogle Scholar
  7. 7.
    Brattico, E., Jacobsen, T., De Baene, W., Glerean, E., Tervaniemi, M.: Cognitive vs. affective listening modes and judgments of music – An ERP study. Biological Psychology 85, 393–409 (2010)CrossRefGoogle Scholar
  8. 8.
    Peretz, Shahin, A., Roberts, L., Chau, W., Trainor, L., Millera, L.: Music training leads to the development of timbre-specific gamma band activity. NeuroImage 41, 113–122 (2008)Google Scholar
  9. 9.
    Cohen, J.D., Perlstein, W.M., Braver, T.S., Nystrom, L.E., Noll, D.C., Jonides, J., Smith, E.E.: Temporal dynamics of brain activation during a working memory task. Nature 386, 604–608 (1997)CrossRefGoogle Scholar
  10. 10.
    Lehmann, A.C., Davidson, J.W.: Taking an acquired skills perspective on music performance. In: Colwell, R., Richardson, C. (eds.) The New Handbook of Research on Music Teaching and Learning, pp. 542–560. Oxford University Press, New York (2002)Google Scholar
  11. 11.
    Woody, R.H.: Explaining expressive performance: Component cognitive skills in an aural modeling task. Journal of Research in Music Education 51, 51–63 (2003)CrossRefGoogle Scholar
  12. 12.
    Anderson, E.W., Potter, K.C., Matzen, L.E., Shepherd, J.F., Preston, G.A., And Silva, C.T.: A User Study of Visualization: Effectiveness Using EEG And Cognitive Load. In: Hauser, H., Pfister, H. (eds.) Eurographics / IEEE Symposium On Visualization 2011 (Eurovis 2011), vol. 30(3) (2011)Google Scholar
  13. 13.
    Hassan, H., Murat, Z.H., Ross, V., Mohd-Zain, Z., Buniyamin, N.: Enhancing Learning Using Music to Achieve a Balanced Brain. In: 3rd International Congress on Engineering Education (ICEED 2011), Kuala Lumpur, Malaysia, December 7- 8, pp. 70–74 (2011)Google Scholar
  14. 14.
    Gazzaniga, M.S.: Cerebral specialization and interhemispheric communication. Does the corpus callosum enable the human condition? A Journal of Neurology 123, 1293–1326 (2000)Google Scholar
  15. 15.
    Gregory, J.: Brain Warmup Exercises forAuthor Creativity (2009),
  16. 16.
    Teplan, M.: Fundamentals of EEG Measurement. Measurement Science Review 2, 1–11 (2002)Google Scholar
  17. 17.
    Manjarrez, E., Vázquez, M., Flores, A.: Computing the center of mass for traveling alpha waves in the human brain. Brain Research, 239–247 (2007)Google Scholar
  18. 18.
    Will, U., Berg, E.: Brain wave synchronization and entrainment to periodic acoustic stimuli. Neuroscience Letters 424, 55–60 (2007)Google Scholar
  19. 19.
    Murat, Z.H., Taib, M.N., Hanafiah, Z.M., Lias, S., Kadir, R.S.S.A., Rahman, H.A.: Initial Investigation of Brainwave Synchronization After Five Sessions of Horizontal Rotation Intervention Using EEG. In: 5th International Colloquium on Signal Processing & Its Applications (CSPA), pp. 350–354 (2009)Google Scholar
  20. 20.
    Sperry, R.W.: Left -Brain, Right Brain. In: Saturday Review: Speech Upon Receiving the Twenty-Ninth Annual Passano Foundation Award, pp. 30–33 (1975)Google Scholar
  21. 21.
    Sperry, R.W.: Some Effects of Disconnecting the Cerebral Hemispheres. In: Division of Biology, California Institute of Technology, Pasadena, California, pp. 1–9 (1981)Google Scholar
  22. 22.
    Will, U., Berg, E.: Brainwave Synchronization and Entrainment to Periodic Acoustic Stimuli. Neuroscience Letters 424, 55–60 (2007)CrossRefGoogle Scholar
  23. 23.
    O’Regan, S., Faul, S., Marnane, W.: Automatic detection of EEG artefacts arising from head movements. In: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, pp. 6353–6356 (2010)Google Scholar
  24. 24.
    Sanei, S., Chambers, J.A.: EEG Signal Processing. Wiley (2007)Google Scholar
  25. 25.
    Adeli, H., Zhou, Z., et al.: Analysis of EEG Records in an Epileptic Patient Using Wavelet Transform. Journal of Neuroscience Methods 123, 69–87 (2003)CrossRefGoogle Scholar
  26. 26.
    Durka, P.: From Wavelets to Adaptive Approximations: Time-Frequency Parametrization of EEG. BioMedical Engineering OnLine 2, 1 (2003)CrossRefGoogle Scholar
  27. 27.
    He Sheng, L., Tong, Z., et al.: A Multistage, Multimethod Approach for Automatic Detection and Classification of Epileptiform EEG. IEEE Transactions on Biomedical Engineering 49, 1557–1566 (2002)CrossRefGoogle Scholar
  28. 28.
    Da-Zeng, T., Ming-Hu, H.: Applications of Wavelet Transform in Medical Image Processing. presented at Machine Learning and Cybernetics (2004)Google Scholar
  29. 29.
    Faro, A., Giordano, D., et al.: Transcranial Magnetic Stimulation (TMS) to Evaluate and Classify Mental Diseases Using Neural Networks. In: Artificial Intelligence in Medicine, pp. 310–314 (2005)Google Scholar
  30. 30.
    Miller, A.S., Blott, B.H., et al.: Review of Neural Network Applications in Medical Imaging and Signal Processing. Medical and Biological Engineering and Computing 30, 449–464 (1992)CrossRefGoogle Scholar
  31. 31.
    Van Dun, B., Wouters, J., et al.: Improving Auditory Steady-State Response Detection Using Independent Component Analysis on Multichannel EEG Data. IEEE Transaction on Biomedical Engineering 54 (2007)Google Scholar
  32. 32.
    Rajapakse, J.C., Cichocki, A., et al.: Independent Component Analysis and Beyond in Brain Imaging: EEG, MEG, fMRI, and PET. In: Proceedings of the 9th International Conference on Neural Information Processing, ICONIP 2002 (2002)Google Scholar
  33. 33.
    Lin, C.T., Chuang, S.W., et al.: EEG Effects of Motion Sickness Induced in a Dynamic Virtual Reality Environment. In: 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2007, pp. 3872–3875 (2007)Google Scholar
  34. 34.
    Juslin, P., Västfjäll, D.: Emotional responses to music: The need to consider underlying mechanisms. Behavioral and Brain Sciences 31, 559–575 (2008)Google Scholar
  35. 35.
    Patterson, R.D., Uppenkamp, S., Johnsrude, I.S., Griffiths, T.D.: The processing of temporal pitch and melody information in auditory cortex. Neuron 36, 767–776 (2002)CrossRefGoogle Scholar
  36. 36.
    Tillmann, B., Janata, P., Bharucha, J.J.: Activation of the inferior frontal cortex in musical priming. Cognitive Brain Research 16, 145–161 (2003)CrossRefGoogle Scholar
  37. 37.
    Hassan, H., Murat, Z.H., Ross, V., Buniyamin, N.: A Preliminary Study on the Effects of Music on Human Brainwaves. In: International Conference on Automation and Information Sciences (ICCAIS 2012), Ho Chi Minh City, Vietnam, December 26-29, pp. 176–180 (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Valerie Ross
    • 1
  • Zunairah Haji Murat
    • 2
  • Norlida Buniyamin
    • 2
  • Zaini Mohd-Zain
    • 3
  1. 1.Faculty of MusicUniversiti Teknologi MARAShah AlamMalaysia
  2. 2.Faculty of Electrical EngineeringUniversiti Teknologi MARAShah AlamMalaysia
  3. 3.Faculty of MedicineUniversiti Teknologi MARAShah AlamMalaysia

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