Prospects for Using Adaptive Biofeedback to Train Musicians

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The use of biofeedback (BFB) technology becomes relevant for professional training of musicians to achieve success in psychomotor function control. We compared two training approaches: 20-22 sessions of alpha-EEG/EMG biofeedback implication to increase the аlpha-2 power while reducing the tension of the forehead muscles and sham biofeedback training. Fifty student musicians (18-28 years old) were divided randomly by age, gender, performing specialty, and individual EEG alpha-peak frequency (IAPF) into two groups. Music performance, state anxiety, self-actualization, nonverbal creativity, coefficient of finger movement optimality (Ko) and the efficiency of the single training session (E1) were evaluated before and after for both types of courses. We calculated the change of the EEG power in the individually adjusted alpha-2 range in the Pz and the integrated EMG power of the surface muscles of the forehead in response to finger movement. Training with biofeedback improved music performance score, increased self-actualization, Ko, and E1 while reducing pre-stage anxiety. The students who received the sham biofeedback did not achieve such improvements. When using biofeedback, students with baseline low alpha-peak frequency (LF) showed a more significant increase in scores for music performance, Ko, and E1 than students with high alpha-peak frequency (HF). In LF students, the sessions without biofeedback did not change the studied parameters. In this pilot placebo-controlled study, we demonstrated that achieving success in the optimal musical performance training depends on the baseline genetically determined IAPF and feedback implication from the EEG alpha-2 power and forehead muscle tone.

About the authors

Tatiana I. Petrenko

Moscow Schnitke State Institute of Music

Author for correspondence.
SPIN-code: 4376-9550
10 Marshala Sokolovskogo St., Moscow, 123060, Russian Federation

Professor, Department of Special Piano Schnitke

Olga M. Bazanova

Scientific Research Institute of Physiology & Basic Medicine

SPIN-code: 9237-2027
4 Timakova St., Novosibirsk, 630117, Russian Federation

Doctor of Biological Sciences, is chief researcher of the Laboratory of Affective, Cognitive and Translational Neuroscience

Muhamed K. Kabardov

Psychological Institute of Russian Academy of Education

9 Mohovaya St., bldg. 4, Moscow, 125009, Russian Federation


  1. Anokhin P.K. (1973). Printsipial’nye voprosy obshchei teorii funktsional’nykh sistem. In P.K. Anohin (Ed.), Printsipy Sistemnoi Organizatsii Funktsii (pp. 5–61) Moscow: Nauka Publ. (In Russ.)
  2. Bazanova, O.M., & Aftanas, L.I. (2006). Uspeshnost’ obucheniya i individual’nye chastotnodinamicheskie kharakteristiki al’fa-aktivnosti EEG. Vestnik RAMN, (6), 30–43. (In Russ.)
  3. Bazanova, O.M., & Aftanas, L.I. (2008). Individual measures of electroencephalogram alpha activity and non-verbal creativity. Neuroscience and Behavioral Physiology, 38(3), 227–235.
  4. Bazanova, O.M., Alekseeva, M.V., Balioz, N.V., Muravleva, K.B., & Sapina, E.V. (2012). Issledovanie treninga proizvol’nogo uvelicheniya al’fa-moshchnosti EEG dlya uluchsheniya kognitivnoi dejatel’nosti. Fiziologiya Cheloveka, 38(1), 51–60. (In Russ.)
  5. Bazanova, O.M., Nikolenko, E.D., & Barry, R.J. (2017). Reactivity of alpha rhythms to eyes opening (the Berger effect) during menstrual cycle phases. Journal of Psychophysiology, 122, 56–64.
  6. Bazanova, O.M., & Vernon, D. (2014). Interpreting EEG alpha activity. Neuroscience & Biobehavioral Reviews, 44, 94–110.
  7. Bernshtejn, N.A. (1947). O Postroenii Dvizhenij. Moscow: Medgiz Publ. (In Russ.)
  8. Bernshtejn, N.A. (1966). Ocherki po Fiziologii Dvizhenij i Fiziologii Aktivnosti. Moscow: Medicina Publ. (In Russ.)
  9. Cacioppo, J.T., & Martzke, J.S., Petty, R.E., & Tassinary, L.G. (1988). By Specific forms of facial EMG response index emotions during an interview: From Darwin to the continuous flow hypothesis of affect-laden information processing. Journal of Personality and Social Psychology, 54(4), 592–604.
  10. Csikszentmihalyi, M., & Larson, R. (2014). Validity and Reliability of the Experience-Sampling Method. In Flow and the Foundations of Positive Psycholog (pp. 79–90). Dordrecht: Springer.
  11. Druzhinin, V.N. (2007). Psikhologiya Obshchikh Sposobnostei. Saint Petersburg: Piter Publ. (In Russ.)
  12. Ebie, B. D. (2004). The effects of verbal, vocally modeled, kinesthetic, and audio-visual treatment conditions on male and female middle-school vocal music students’ abilities to expressively sing melodies. Journal of Psychology of Music, (32), 405–417.
  13. Golubeva, E.A. (2005). Sposobnosti, Lichnost’, Individual’nost’. Dubna: Feniks Publ. (In Russ.)
  14. Grigorev, V.Yu. (2006). Ispolnitel’ i Estrada. Moscow: Mos. gos. kons. Publ., Magnitog. gos. kons. Publ. (In Russ.)
  15. Gruzelier, J. (2014). EEG-neurofeedback for optimising performance. II: creativity, the performing arts and ecological validity. Journal of Psychophysiology, 93(1), 96–104.
  16. Hale, M. (1993). EMG Biofeedback of the Abductor Pollicis Bravis in Piano Performance. Journal of Biofeedback and Self Regulation, 18(2), 67–77.
  17. Kabardov, M.K., Bazanova, O.M., Lebedev, A.N., & Kondratenko, A.V. (2011). Zavisimost’ elektrofiziologicheskikh priznakov muzykal’no-ispolnitel’skikh sposobnostei ot vozrasta, pola i neirogumoral’nogo statusa. In Sovremennoe Sostoyanie Differencial’noj Psikhologii i Differencial’noj Psihofiziologii: Proceedings of the Conference to the 115th Anniversary of B. Teplov (pp. 57–59). Moscow: Psychological Institute of RAE Publ. (In Russ.)
  18. Kabardov, M.K., Simakova, I.N., Toropova, A.V., & Vasilevskaya, K.N. (2013). Psihofiziologicheskie indikatory muzykal’nosti. Vestnik YUNESKO: Muzykal’noe Iskusstvo i Obrazovanie, (3), 116–121. (In Russ.)
  19. Khanin, Yu.L. (1976). Kratkoe rukovodstvo k shkale reaktivnoi i lichnostnoi trevozhnosti Ch.D. Spilbergera. Leningrad: LNIIFK Publ. (In Russ.)
  20. Klimesch, W., Sauseng, P., & Hanslmayr, S. (2007). EEG alpha oscillations: The inhibitiontiming hypothesis. Journal of Brain Research, (53), 63–88.
  21. Kraus, E. (1982–1983). Studying Music in the Federal Republic of Germany: Study Guide. Mainz, London, New York, Tokyo: Schott.
  22. Lazareva, O.Y., Muravleva, K.B., Skoraya, M.V., Verevkin, E.G., & Bazanova, O.M. (2012). The influence of self-regulation technique on the efficiency of voluntary increasing alpha power training. International Journal of Psychophysiology, 85(3), 344. doi: 10.1016/j. ijpsycho.2012.06.146
  23. Lehmann A.C. (1997). Acquired mental representations in music performance: anecdotal and preliminary empirical evidence (pp. 141–163). Oslo: Norwegian State Academy of Music. Lehmann, A.C., Platz, F., Kopiez, R., & Wolf, A. (2014). The influence of deliberate practice on musical achievement: A meta-analysis. Journal Frontiers in Psychology, 5, 646.
  24. Malisova, D.V., Petrenko, T.I., Kondratenko, A.V., & Bazanova, O.M. (2017). Al’fa EEG i EMG priznaki optimal’nosti muzykal’no-ispolnitel’skogo dvizheniya i postural’nyi kontrol’. Materialy XXIII S”ezda Rossijskogo Fiziologicheskogo Obshchestva imeni I.P. Pavlova (pp. 967–968). Voronezh: Voronezh State Medical University named after N.N. Burdenko. (In Russ.)
  25. Malmo, R.B., & Malmo, H.P. (2000). On electromyographic (EMG) gradients and movementrelated brain activity: significance for motor control, cognitive functions, and certain psychopathologies. International Journal of Psychophysiology, 38, 143–207. https://doi. org/10.1016/S0167-8760(00)00113-6
  26. Malyh, S.B. (1997). Issledovaniya geneticheskoi determinatsii EEG cheloveka. Voprosy Psihologii, (6), 109–128. (In Russ.)
  27. Merletti, R. (1999). Standards for Reporting EMG data. Journal of Electromyography and Kinesiology, (9), III–IV.
  28. Mierau, A., Klimesch, W., & Lefebvre, J. (2017). State-dependent alpha peak frequency shifts: Experimental evidence, potential mechanisms and functional implications. Journal of Neuroscience, 360, 146–154.
  29. Nagel, T., (1986). The View From Nowhere. Oxford: University Press. Naito, A., Sun, Y.J., Yajima, M., Fukamachi, H., & Ushikoshi, K. (1998). Electromyographic study of the elbow flexors and extensors in a motion of forearm pronation/supination
  30. while maintaining elbow flexion in humans. The Tohoku Journal of Experimental Medicine, 186(4), 267–777.
  31. Osnitskii, A.K. (2010). Psihologicheskie Mekhanizmy Samostoyatel’nosti. Obninsk: IG-SOTSIN Publ. (In Russ.)
  32. Rheinberg, F., Vollmeyer, R., & Engeser, S. (2003). Die Erfassung des Flow-Erlebens. In J. Stiensmeier-Pelster & F. Rheinberg (Eds.). Handbook of Diagnostik von Motivation und Selbstkonzept (Tests und Trends N.F. Bd.2) (pp. 261–279). Göttingen: Hogrefe.
  33. Sterman, M.B. (1996). Physiological origins and functional correlates of EEG rhythmic activities: implications for self-regulation. Journal of Biofeedback and Self Regulation, 21(1), 3–33.
  34. Stukolkina, S. (2007). Put’ k Sovershenstvu. Dialogi, stat’i i materialy o fortepiannoi tekhnike. Saint Petersburg: Kompozitor Publ. (In Russ.)
  35. Talalai, B.N. (1982). Formirovanie Ispolnitel’skih (Dvigatel’no-Tekhnicheskih) Navykov pri Obuchenii Igre na Muzykal’nyh Instrumentakh. PhD in Education Thesis Abstract. Moscow. (In Russ.)
  36. Teplov, B.M. (2009). Psikhologiya i Psikhofiziologiya Individual’nykh Razlichii: Selected Psychological Works. Moscow: Moskovskii psikhologo-sotsial’nyi institute Publ.; Voronezh: NPO “MODEK” Publ. (In Russ.)
  37. Tsypin, G.M. (2018). Psikhologiya Tvorcheskoi Deyatel’nosti. Muzyka i Drugie Iskusstva. Moscow: Yurait Publ. (In Russ.)



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Copyright (c) 2019 Petrenko T.I., Bazanova O.M., Kabardov M.K.

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