Enhancing Creativity with Neurofeedback in the Performing Arts: Actors, Musicians, Dancers

  • John H. GruzelierEmail author
Part of the Creativity Theory and Action in Education book series (CTAE, volume 2)


Applications of EEG-neurofeedback to the performing arts with actors are reviewed and compared with relevant studies of musicians and dancers. Neurofeedback involves learning to self-regulate targeted brain rhythms, rhythms that here have putative relevance to artistic performance. Actors received sensory-motor rhythm training, theorised to favour authenticity in acting, with a training context immersing them in an onstage theatre auditorium through either 2D or 3D representation. The more immersive format led to superior acting according to experts, especially on creativity subscales. Furthermore the actors’ experience of flow in performance was superior following neurofeedback, with affirmative associations between subjective flow and objective expert ratings. A slow wave protocol which involves training-up the theta rhythm over alpha with eyes closed before entering sleep (see Sect. 14.1) showed consistent benefits for elite music performance, especially musicality/creativity and extending to communication and technique. This benefit was also found with novice performers, to include school children, where the sensory-motor rhythm protocol also enhanced performance, perhaps facilitating lower-lever processes such as attention, memory and psychomotor skill. With competitive ballroom and contemporary dancers the alpha/theta protocol was compared with heart rate coherence biofeedback; both interventions were of value. The evidence adds to the rapidly accumulating validation of neurofeedback, while performing arts studies offer an opportunity for real life validity in creativity research for both creative process and product.


Neurofeedback EEG Creativity Acting Music Dance 


  1. Arns, M., Heinrich, H., & Strehl, U. (2014). Evaluation of neurofeedback: The long and winding road. Biological Psychology, 95, 108–115.CrossRefGoogle Scholar
  2. Arns, M. W., de Ridder, S., Strehl, U., Breteler, M. H. M., & Coenen, A. M. L. (2009). Efficacy of neurofeedback treatment on ADHD: The effect on inattention, impulsivity and hyperactivity: A meta-analysis. Clinical EEG and Neuroscience, 40, 180–189.CrossRefGoogle Scholar
  3. Barlow, W. (1980). The Alexander technique. New York: Warner Books.Google Scholar
  4. Berberian, C. (1966). Stripsody. New York: C.F. Peters Corporation.Google Scholar
  5. Boynton, T. (2001). Applied research using alpha/theta training for enhancing creativity and well-being. Journal of Neurotherapy, 5(1–2), 5–18.CrossRefGoogle Scholar
  6. Creech, A., Papageorgi, I., Duffy, C., Morton, F., Hadden, E., Potter, J., De Bezenac, C., Whyton, T., Himonides, E., Welch, G. (2008). Investigating musical performance: Commonality and diversity among classical and non-classical musicians. Music Education Research, 10(2), 215–234.CrossRefGoogle Scholar
  7. Csíkszentmihályi, M. (1996). Creativity: Flow and the psychology of discovery and invention. New York: HarperCollins Publishers.Google Scholar
  8. Doppelmayr, M., & Weber, E. (2011). Effects of SMR and theta/beta neurofeedback on reaction time, spatial abilities and creativity. Journal of Neurotherapy, 15(2), 115–129.CrossRefGoogle Scholar
  9. Dow, G., & Mayer, R. (2004). Teaching students to solve insight problems: Evidence for domain specificity in creativity training. Creativity Research Journal, 16(4), 389–402.CrossRefGoogle Scholar
  10. Edge, J., & Lancaster, B. L. (2004). Enhancing musical performance through neurofeedback: Playing the tune of life. Transpersonal Psychology Review, 8(1), 23–35.Google Scholar
  11. Egner, T., & Gruzelier, J. H. (2001). Learned self-regulation of EEG frequency components affects attention and event-related brain potentials in humans. Neuroreport, 12(18), 4155–4159.CrossRefGoogle Scholar
  12. Egner, T., & Gruzelier, J. H. (2003). Ecological validity of neurofeedback: Modulation of slow wave EEG enhances musical performance. Neuroreport, 14(9), 1221–1224.CrossRefGoogle Scholar
  13. Egner, T., & Gruzelier, J. H. (2004). EEG biofeedback of low beta band components: Frequency-specific effects on variables of attention and event-related brain potentials. Clinical Neurophysiology, 115(1), 131–139.CrossRefGoogle Scholar
  14. Fink, A., Graif, B., & Neubauer, A. C. (2009). Brain correlates underlying creative thinking: EEG alpha activity in professional vs. novice dancers. NeuroImage, 46(3), 854–862.CrossRefGoogle Scholar
  15. Frost, A., & Yarrow, R. (2015). Improvisation in drama, theatre and performance: History, practice, theory. New York: Palgrave MacMillan Education.Google Scholar
  16. Gordon, C. M., & Gruzelier, J. (2003). Self-hypnosis and osteopathic soft tissue manipulation with a ballet dancer. Contemporary Hypnosis, 20(4), 209–214.CrossRefGoogle Scholar
  17. Gruzelier, J. H. (2014a). EEG-neurofeedback for optimising performance. I: A review of cognitive and affective outcome in healthy participants. Neuroscience and Biobehavioral Reviews, 44, 124–141.CrossRefGoogle Scholar
  18. Gruzelier, J. H. (2014b). EEG-neurofeedback for optimising performance. II: Creativity, the performing arts and ecological validity. Neuroscience and Biobehavioral Reviews, 44, 142–158.CrossRefGoogle Scholar
  19. Gruzelier, J. H. (2014c). EEG-neurofeedback for optimising performance. III: A review of cognitive and affective outcome in healthy participants. Neuroscience and Biobehavioral Reviews, 44, 159–182.CrossRefGoogle Scholar
  20. Gruzelier, J. H. (2014d). Differential effects on mood of 12–15 (SMR) and 15–18 (beta1) Hz neurofeedback. International Journal of Psychophysiology, 93(1), 112–115.CrossRefGoogle Scholar
  21. Gruzelier, J. H., & Egner, T. (2004). Physiological self-regulation: Biofeedback and neurofeedback. In A. Williamon (Ed.), Musical excellence: Strategies and techniques to enhance performance (pp. 197–219). Oxford: Oxford University Press.Google Scholar
  22. Gruzelier, J. H., Inoue, A., Steed, A., & Steffert, T. (2010). Acting performance and flow state enhanced with sensory-motor rhythm neurofeedback comparing ecologically valid immersive VR and training screen scenarios. Neuroscience Letters, 480(2), 112–116.CrossRefGoogle Scholar
  23. Gruzelier, J. H., Holmes, P., Hirst, L., Bulpin, K., Rahman, S., van Run, C., & Leach, J. (2014a). Replication of elite music performance enhancement following alpha/theta neurofeedback with application to improvisation and novice performance as well as SMR benefits. Biological Psychology, 95, 96–107.CrossRefGoogle Scholar
  24. Gruzelier, J. H., Foks, M., Steffert, T., Chen, M. J., & Ros, T. (2014b). Beneficial outcome from EEG-neurofeedback on creative music performance, attention and well-being in school children. Biological Psychology, 95, 86–95.CrossRefGoogle Scholar
  25. Gruzelier, J. H., Thompson, T., Redding, E., Brandt, R., & Steffert, T. (2014c). Application of alpha/theta neurofeedback and heart rate variability training to young contemporary dancers: State anxiety and creativity. International Journal of Psychophysiology, 93(1), 105–111.CrossRefGoogle Scholar
  26. Guilford, J. P. (1967). The nature of human intelligence. New York: McGraw-Hill.Google Scholar
  27. Harvey, J. (1994). These music exams. London: Associated Board of the Royal Schools of Music.Google Scholar
  28. Jackson, S. A., & Eklund, R. C. (2004). The flow scales manual. Morgantown: Fitness Information Technology.Google Scholar
  29. Jausovec, N., & Jausovec, K. (2011). Brain, creativity and education. The Open Educational Journal, 4, 50–57.CrossRefGoogle Scholar
  30. Koestler, A. (1964). The act of creation. London: Hutchinson & Co.Google Scholar
  31. Lovibond, S. H., & Lovibond, P. F. (1995). Manual for the depression, anxiety, stress scales (2nd ed.). Sydney: Psychology Foundation of Australia.Google Scholar
  32. Martindale, C. (1999). Biological bases of creativity. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 137–152). Cambridge: Cambridge University Press.Google Scholar
  33. Noy, L., Dekel, E., & Alon, U. (2011). The mirror game as a paradigm for studying the dynamics of two people improvising motion together. Proceedings of the National Academy of the Sciences of the United States, 108(52), 20947–20952.CrossRefGoogle Scholar
  34. Piffer, D. (2012). Can creativity be measured? An attempt to clarify the notion of creativity and general directions for future research. Thinking Skills and Creativity, 7(3), 258–264.CrossRefGoogle Scholar
  35. Raymond, J., Sajid, I., Parkinson, L. A., & Gruzelier, J. H. (2005). Biofeedback and dance performance: A preliminary investigation. Applied Psychophysiology and Biofeedback, 30(1), 64–73.CrossRefGoogle Scholar
  36. Ros, T., Moseley, M. J., Bloom, P., Benjamin, L., Parkinson, L., & Gruzelier, J. H. (2009). Optimizing microsurgical skills with EEG neurofeedback. BMC Neuroscience, 10, 87–97. Scholar
  37. Runco, M. A., & Bahleda, M. D. (1986). Implicit theories of artistic, scientific, and everyday creativity. Journal of Creative Behavior, 20(2), 93–98.CrossRefGoogle Scholar
  38. Sawyer, R. K. (2000). Improvisation and the creative process: Dewey, Collingwood, and the aesthetics of spontaneity. The Journal of Aesthetics and Art Criticism, 58(2), 149–161.CrossRefGoogle Scholar
  39. Spielberger, C. D., Gorsuch, R. L., Lushene, R. E., Vagg, P. R., & Jacobs, G. A. (1983). Manual for the state-trait anxiety inventory. Palo Alto: Consulting Psychologists Press.Google Scholar
  40. Sternberg, R. J. (1985). Implicit theories of intelligence, creativity and wisdom. Journal of Personality and Social Psychology, 49(3), 607–627.CrossRefGoogle Scholar
  41. Thayer, R. E. (1967). Measurement of activation through self-report. Psychological Reports, 20(2), 663–678.CrossRefGoogle Scholar
  42. Thompson, S., & Williamon, A. (2003). Evaluating evaluation: Musical performance assessment as a research tool. Music Perception, 21(1), 21–41.CrossRefGoogle Scholar
  43. Thompson, W. F., Diamond, C. P., & Balkwill, L. L. (1998). The adjudication of six performances of a Chopin étude: A study of expert knowledge. Psychology of Music, 26(2), 154–174.CrossRefGoogle Scholar
  44. Wapnick, J., & Ekholm, E. (1997). Expert consensus in solo voice performance evaluation. Journal of Voice, 11(4), 429–436.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Goldsmiths University of LondonLondonUK

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