The autotelic involvement of attention induced by EEG neurofeedback training improves the performance of an athlete’s mind

Mikicin, Mirosław

doi:10.1515/bhk-2015-0010

Abstract

immediate feedback concerning brain activity on autotelic engagement attention and the performance of athletes’ minds.

Material and methods: the experimental group (25 subjects) underwent twenty neurofeedback-EEG training sessions (in the relaxation armchair) and athletic training for four months (every 7 days). The control group (25 subjects) underwent athletic training sessions. Before and after the four months of neurofeedback-EEG training sessions, the athletes were evaluated using an involvement questionnaire and Kraepelin’s work curve test.

Results: the results of the analysis showed that changes in autotelic engagement were observed with an improvement in the performance of the mind (p < 0.01), which points to increased speed and mental work speed and efficiency. Among three measures of performance, we observed a significant correlation between the total number of addition operations in the test with autotelic experience (r = 0.769).

Conclusions: neurofeedback-EEG training opens up new opportunities for improvement in the performance of athletes’ minds.

References

1. Asakawa K., Csikszentmihalyi M. (2000) Feelings of connectedness and internalization of values in Asian American adolescents. J. Youth Adolesc., 29: 121–145.
Search in Google Scholar
2. Asakawa K. (2004) Flow experience and autotelic personality in Japanese college students: how do they experience challenges in daily life? J. Happiness Stud., 5: 123–154.10.1023/B:JOHS.0000035915.97836.89
Search in Google Scholar
3. Arnold W. (1975) Der Pauli-Test. Anweisung zur sachgemäßen durchführung, Auswertung und Anwendung des Kraepelinschen Arbeitsbesuches 5, korrigierte Aufl. Springer-Verlag: Berlin, 1–184.10.1007/978-3-642-66233-1
Search in Google Scholar
4. Bazanova O.M., Mernaya E.M., Shtark M.B. (2009) Biofeedback in psychomotor training. Electrophysiologic.Basis Neurosci. Behav. Physiol., 39(5): 437–448.10.1007/s11055-009-9157-z
Search in Google Scholar
5. Besserve M., Philippe M., Florence G., Laurent F., Garnero L., Martinerie J. (2008) Prediction of performance level during a cognitive task from ongoing EEG oscillatory activities. Clin. Neurophysiol., 119: 897–908.
Search in Google Scholar
6. Bradley R.T., McCraty R., Atkinson M., Tomasino D., Daugherty A., Arguelles L. (2010) Emotion self-regulation, psychophysiological coherence, and test anxiety: results from an experiment using electrophysiological measures. Appl. Psychophysiol. Biofeedback, 35(4): 261–83.10.1007/s10484-010-9134-x
Search in Google Scholar
7. Brandstätter H. (1995) Die Arbeitskurve nach Kraepelin-Pauli – doch ein Willenstest? Zeitschrift für Arbeits – und Organisationspsychologie, 39: 54–66.
Search in Google Scholar
8. Csikszentmihalyi M. (1988) The flow experience and its significance for human psychology. In: M. Csikszentmihalyi, I.S. Csikszentmihalyi (eds.), Optimal Experience: Psychological Studies of Flow in Consciousness. Cambridge University Press: New York, 15–35.10.1017/CBO9780511621956.002
Search in Google Scholar
9. Csikszentmihalyi M., LeFevre J. (1989) Optimal experience in work and leisure. J. Personal. Social Psychol., 56: 815–822.
Search in Google Scholar
10. Csikszentmihalyi M., Rathunde K. (1993) The measurement of flow in everyday life. Nebraska Symposium on Motivation, 40: 57–97.
Search in Google Scholar
11. 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. Clin, Neurophysiol., 115: 131–139.10.1016/S1388-2457(03)00353-5
Search in Google Scholar
12. Fan J., Byrne J., Worden M.S., Guise K.G., McCandliss B.D., Fossella J., Posner M.I. (2007) The relation of brain oscillations to attentional networks. J. Neurosci., 27: 6197–6206.
Search in Google Scholar
13. Fournier J. (2007) French translation of flow state scale-2: factor structure, cross-culture invariance, and associations with goal attainment. Psychol. Sport Exerc., 8: 897–916.
Search in Google Scholar
14. Gibson A., Boulton M.G., Watson M.P., Moseley M.J., Murray P.I., Fielder A.R. (2005) The first cut is the deepest: basic surgical training in ophthalmology. Eye, 19: 1264–1270.10.1038/sj.eye.6701754
Search in Google Scholar
15. Gruzelier J.H., Egner T., Vernon D. (2006) Validating the efficacy of neurofeedback for optimizing performance. Progress in Brain Research, 159: 421–431.10.1016/S0079-6123(06)59027-2
Search in Google Scholar
16. Hammond D.C. (2007) Neurofeedback for the enhancement of athletic performance and physical balance. J. Amer. Board Sport Psychol., 1: 27–36.
Search in Google Scholar
17. Hanslmayr S., Sauseng P., Doppelmayr M., Schabus M., Klimesch W. (2005) Increasing individual upper alpha power by neurofeedback improves cognitive performance in human subjects. Appl. Psychophysiol. Biofeedback, 30: 1–10.
Search in Google Scholar
18. Kwabata M. (2008) The flow state scale-2 and dispositional flow scale-2: Examination of factorial validity and reliability for Japan’s adults. Psychol. Sport Exerc., 9: 465–485.
Search in Google Scholar
19. Kashiwagi S., Tanaka Y., Tsubokura K., Okuyama K., Shinrigaku K. (2007) Evaluation of the Uchida-kraepelin psycho-diagnostic test based on addition work from the view of the Big Five. Josai International University, 78: 125–132.
Search in Google Scholar
20. Kerick S.E., Douglass L.W., Hatfield B.D. (2004) Cerebral cortical adaptations associated with visuomotor practice. Med. Sci. Sports Exerc., 1: 118–129.
Search in Google Scholar
21. Kraepelin E. (1922) Gedanken über die Arbeitskurve, Psychologische Arbeiten, 7: 535–547.
Search in Google Scholar
22. Larsen C.R., Soerensen J.L., Grantcharov T.P., Dalsgaard T., Schouenborg L., Ottosen C., Schroeder T.V., Ottesen B.S. (2009) Effect of virtual reality training on laparoscopic surgery: randomized controlled trial. BMJ, 14: 1802.10.1136/bmj.b1802327378219443914
Search in Google Scholar
23. Leff D., Aggarwal R., Rana M., Nakhjavani B., Purkayastha S., Khullar V., Darzi A.W. (2008) Laparoscopic skills suffer on the first shift of sequential night shifts: program directors beware and residents prepare. Ann. Surg., 247: 530–539.10.1097/SLA.0b013e3181661a9918376200
Search in Google Scholar
24. McCrae R.R., Terracciano A. (2008) The Five Factor Model and its correlates in individuals and cultures. In Van de Vijver F.J.R., van Hemert D.A., Poortinga Y.H. (eds.), Individuals and cultures in multi-level analysis. Mahwah, NJ: Erlbaum, 247–281.
Search in Google Scholar
25. Mikicin M. (2007) Relationships between experiencing flow state and personality traits, locus of control and achievement motivation in swimmers. Phys. Edu. Sport, 4: 315–322.
Search in Google Scholar
26. Mikicin M. (2013) Autotelic personality as a predictor of engagement in sports. Biomed. Hum. Kinet., 5: 65–71.
Search in Google Scholar
27. Mikicin M. (2014) Work curve as a distinguishing mark of athletes’ work performance. Biomed. Hum. Kinet., 6: 69–76.
Search in Google Scholar
28. Monastra V.J. (2005) Electroencephalographic biofeedback (neurotherapy) as a treatment for attention deficit hyperactivity disorder: rationale and empirical foundation. Child and Adolescent Psychiatric Clinics of North America, 14(1): 55–82.10.1016/j.chc.2004.07.00415564052
Search in Google Scholar
29. Raymond J., Sajid I., Parkinson L.A., Gruzelier J.H. (2005) Biofeedback and dance performance: a preliminary investigation. Appl. Psychophysiol. Biofeedback, 30: 65–73.
Search in Google Scholar
30. Saleh G.M., Voyazis Y., Hance J., Ratnasothy J., Darzi A. (2006) Evaluating surgical dexterity during corneal suturing. Archives of Ophthalmology, 124: 1263–1266.10.1001/archopht.124.9.126316966621
Search in Google Scholar
31. Sobral D.T. (2004). What kind of motivation drives medical students’ learning quests? Med. Edu., 9: 950–957.
Search in Google Scholar
32. Steinborn M.B., Flehmig H.C., Westhoff K., Langner R. (2009) Differential effects of prolonged work on performance measures in self-paced speed tests. Adv. Cogn. Psychol., 5: 105–113.
Search in Google Scholar
33. Sugden C., Aggarwal R., Darzi R. (2010) Sleep deprivation, fatigue, medical error and patient safety. Amer. J. Surg., 199(3): 433–434.10.1016/j.amjsurg.2009.03.00119427627
Search in Google Scholar
34. Sugimoto K., Kanai A., Shoji N. (2009) The effectiveness of the Uchida-Kraepelin test for psychological stress: an analysis of plasma and salivary stress substances. Biopsychosocial Medicine, 3: 5–15.10.1186/1751-0759-3-5267905819341484
Search in Google Scholar
35. Takigasaki T. (2006) The work curves of Uchida – Kraepelin test in the time of mountaineering. Nippon Institute of Technology Research Report, 35(3/4): 7–12.
Search in Google Scholar
36. Van Herzeele I., Aggarwal R., Neequaye S., Darzi A., Vermassen F., Cheshire N.J. (2008) Cognitive training improves clinically relevant outcomes during simulated endovascular procedures. J. Vasc. Surg., 48: 1223–1230.
Search in Google Scholar
37. Vecina M.L., Chacón F. (2013) Is engagement different from satisfaction and organizational commitment? Relations with intention to remain, psychological well-being and perceived physical health in volunteers. An. Psicol., 29(1): 225–232.
Search in Google Scholar
38. Vernon D.J., Egner T., Cooper N., Compton T., Neilands C., Sheri A. (2003) The effect of training distinct neurofeedback protocols on aspects of cognitive performance. J. Psychophysiol., 47: 75–85.
Search in Google Scholar
39. Vernon D.J. (2005) Can neurofeedback training enhance performance? An evaluation of the evidence with implications for future research. Appl. Psychophysiol. Biofeedback, 30: 347–364.
Search in Google Scholar
40. Zijlstra A., Mancini M., Chiari L., Zijlstra W. (2010) Biofeedback for training balance and mobility tasks in older populations: a systematic review. J. Neuroeng. Rehabil., 7: 58–73.
Search in Google Scholar

The autotelic involvement of attention induced by EEG neurofeedback training improves the performance of an athlete’s mind

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