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The Analysis of Electroencephalography Changes Before and After a Single Neurofeedback Alpha/Theta Training Session in University Students

Abstract

The underlying mechanisms of alpha/theta neurofeedback training have not been fully determined. Therefore, this study aimed to test the changes in the brain state feedback during the alpha/theta training. Twenty-seven healthy participants were trained during a single session of the alpha/theta protocol, and the resting quantitative electroencephalography (QEEG) was assessed before and after training. QEEG was recorded at eight scalp locations (F3, F4, C3, C4, T3, T4, O1, and O2), and the absolute power, relative power, ratio of sensory-motor rhythm beta (SMR) to theta (RST), ratio of SMR-mid beta to theta (RSMT), ratio of mid beta to theta (RMT), ratio of alpha to high beta (RAHB), and scaling exponent of detrended fluctuation analysis by each band were measured. The results indicated a significant increase of absolute alpha power, especially the slow alpha band, at all electrodes except T3 and T4. Moreover, the relative alpha power, especially the slow alpha band, showed a significant increase at all electrodes. The relative theta power showed a significant decrease at all electrodes, except T3. A significant decrease in relative beta power, relative lower beta power and relative mid beta power was observed at O1. RST (at C4, O1, and O2), RSMT and RMT (at F4, C4, O1 and O2), and RAHB (at all electrodes) showed significant increase. Scaling exponents at all electrodes except T3 showed a significant decrease. These findings indicate that a one-time session of alpha/theta training might have the possibility to enhance both vigilance and concentration, thus stabilizing the overall brain function.

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References

  • Abenson, M. H. (1970). EEGs in chronic schizophrenia. British Journal of Psychiatry, 116(533), 421–425.

    Article  Google Scholar 

  • Aftanas, L. I., & Golocheikine, S. A. (2001). Human anterior and frontal midline theta and lower alpha reflect emotionally positive state and internalized attention: High-resolution EEG investigation of meditation. Neuroscience Letters, 310(1), 57–60.

    PubMed  Article  Google Scholar 

  • Aftanas, L. I., & Golocheikine, S. A. (2002). Non-linear dynamic complexity of the human EEG during meditation. Neuroscience Letters, 330(2), 143–146.

    PubMed  Article  Google Scholar 

  • American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders: DSM-IV-TR. Washington, DC: American Psychological Association.

    Google Scholar 

  • Baehr, E., Rosenfeld, J. P., & Baehr, R. (2001). Clinical use of an alpha asymmetry neurofeedback protocol in the treatment of mood disorders: Follow-up study one to five years post therapy. Journal of Neurotherapy, 4(4), 11–18.

    Article  Google Scholar 

  • Banquet, J.-P. (1973). Spectral analysis of the EEG in meditation. Electroencephalography and Clinical Neurophysiology, 35(2), 143–151.

    PubMed  Article  Google Scholar 

  • Barnea, A., Rassis, A., & Zaidel, E. (2005). Effect of neurofeedback on hemispheric word recognition. Brain and Cognition, 59(3), 314–321.

    PubMed  Article  Google Scholar 

  • Beck, A. T., Epstein, N., Brown, G., & Steer, R. A. (1988a). An inventory for measuring clinical anxiety: Psychometric properties. Journal of consulting and clinical Psychology, 56(6), 893.

    PubMed  Article  Google Scholar 

  • Beck, A. T., & Steer, R. (1993). Beck anxiety inventory manual. San Antonio, TX: The Psychological Corporation.

    Google Scholar 

  • Beck, A. T., Steer, R. A., & Carbin, M. G. (1988b). Psychometric properties of the beck depression inventory: Twenty-five years of evaluation. Clinical Psychology Review, 8(1), 77–100.

    Article  Google Scholar 

  • Beck, A. T., Ward, C. H., Mendelson, M., Mock, J., & Erbaugh, J. (1961). An inventory for measuring depression. Archives of General Psychiatry, 4(6), 561–571.

    PubMed  Article  Google Scholar 

  • Cahn, B. R., & Polich, J. (2006). Meditation states and traits: EEG, ERP, and neuroimaging studies. Psychological Bulletin, 132(2), 180–211.

    PubMed  Article  Google Scholar 

  • Carmody, D. P., Radvanski, D. C., Wadhwani, S., Sabo, M. J., & Vergara, L. (2000). EEG biofeedback training and attention-deficit/hyperactivity disorder in an elementary school setting. Journal of Neurotherapy, 4(3), 5–27.

    Article  Google Scholar 

  • Choi, H., Lee, H. J., & Lee, H. Y. (2017). The effects of torture-related stressors on long-term complex post-traumatic symptoms in South Korean torture survivors. International Journal of Psychology, 52, 57–66.

    PubMed  Article  Google Scholar 

  • Cowan, J., & Allen, T. (2000). Using brainwave biofeedback to train the sequence of concentration and relaxation in athletic activities. Proceedings of 15th Association for the Advancement of Applied Sport Psychology, 95.

  • Cuevas, C. D. L., Arredondo, M. T., Cabrera, M. F., Sulzenbacher, H., & Meise, U. (2006). Randomized clinical trial of telepsychiatry through videoconference versus face-to-face conventional psychiatric treatment. Telemedicine Journal & e-Health, 12(3), 341–350.

    Article  Google Scholar 

  • Derogatis, L. R. (1979). Symptom checklist-90-revised (SCL-90-R). Lyndhurst, NJ: NCS Pearson.

    Google Scholar 

  • Derogatis, L. R. (1992). SCL-90-R: Administration, scoring and procedures manual for the R (evised) version and other instruments of the psychopathology rating scale series. Towson: Clinical Psychometric Research.

    Google Scholar 

  • Egner, T., & Gruzelier, J. H. (2003). Ecological validity of neurofeedback: Modulation of slow wave EEG enhances musical performance. Neuroreport, 14(9), 1221–1224.

    PubMed  Article  Google Scholar 

  • Egner, T., & Gruzelier, J. H. (2004). The temporal dynamics of electroencephalographic responses to alpha/theta neurofeedback training in healthy subjects. Journal of Neurotherapy, 8(1), 43–57.

    Article  Google Scholar 

  • Egner, T., Strawson, E., & Gruzelier, J. H. (2002). EEG signature and phenomenology of alpha/theta neurofeedback training versus mock feedback. Applied Psychophysiology and Biofeedback, 27(4), 261–270.

    PubMed  Article  Google Scholar 

  • Ghaziri, J., Tucholka, A., Larue, V., Blanchette-Sylvestre, M., Reyburn, G., Gilbert, G., et al. (2013). Neurofeedback training induces changes in white and gray matter. Clinical EEG and Neuroscience, 44(4), 265–272.

    PubMed  Article  Google Scholar 

  • Gifani, P., Rabiee, H., Hashemi, M., Taslimi, P., & Ghanbari, M. (2007). Optimal fractal-scaling analysis of human EEG dynamic for depth of anesthesia quantification. Journal of the Franklin Institute, 344(3), 212–229.

    Article  Google Scholar 

  • Globus, G. G., & Arpaia, J. P. (1994). Psychiatry and the new dynamics. Biological Psychiatry, 35(5), 352–364.

    PubMed  Article  Google Scholar 

  • Gruzelier, J. (2009). A theory of alpha/theta neurofeedback, creative performance enhancement, long distance functional connectivity and psychological integration. Cognitive Processing, 10(Suppl 1), S101–S109.

    PubMed  Article  Google Scholar 

  • Gruzelier, J. H. (2014). EEG-neurofeedback for optimising performance. II: Creativity, the performing arts and ecological validity. Neuroscience and Biobehavioral Reviews, 44, 142–158.

    PubMed  Article  Google Scholar 

  • Gündel, H., Wolf, A., Xidara, V., Busch, R., & Ceballos-Baumann, A. (2001). Social phobia in spasmodic torticollis. Journal of Neurology, Neurosurgery & Psychiatry, 71(4), 499–504.

    Article  Google Scholar 

  • Hammond, D. C. (2000). Neurofeedback treatment of depression with the Roshi. Journal of Neurotherapy, 4(2), 45–56.

    Article  Google Scholar 

  • Hammond, D. C. (2005). Neurofeedback with anxiety and affective disorders. Child and Adolescent Psychiatric Clinics of North America, 14(1), 105–123.

    PubMed  Article  Google Scholar 

  • Han, H. M., Yum, T. H., Shin, Y. W., Kim, K. H., Yoon, D. J., & Jung, G. J. (1986). The standardized study of the Korean version of beck depression inventory. Journal of Korean Neuropsychiatric Association, 25(3), 487–502.

    Google Scholar 

  • Hardt, J. V., & Kamiya, J. (1978). Anxiety change through electroencephalographic alpha feedback seen only in high anxiety subjects. Science, 201(4350), 79–81.

    PubMed  Article  Google Scholar 

  • Hirai, T., & Johnston, W. (1974). Psychophysiology of zen. Tokyo: Igaku Shoin.

    Google Scholar 

  • Imai, R., & Okamoto, Y. (2008). [Detection of mental task-induced changes in EEG patterns by detrended fluctuation analysis (DFA)]. Rinsho Byori. Japanese Journal of Clinical Pathology, 56(5), 383–386.

    PubMed  Google Scholar 

  • Jacobs, G. D., & Lubar, J. F. (1989). Spectral analysis of the central nervous system effects of the relaxation response elicited by autogenic training. Behavioral Medicine, 15(3), 125–132.

    PubMed  Article  Google Scholar 

  • Jiang, Z., Ning, Y., An, B., Li, A., & Feng, H. (2005). Detecting mental EEG properties using detrended fluctuation analysis. Conference Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2, 2017–2020.

  • Kasamatsu, A., & Hirai, T. (1966). An electroencephalographic study on the Zen meditation (Zazen). Psychiatry and Clinical Neurosciences, 20(4), 315–336.

    Article  Google Scholar 

  • Kim, K., Kim, J., & Won, H. (1984). Korean version of Symptom Checklist-90-Revised (SCL-90-R) professional manual: Seoul. Seoul: ChoongAng Aptitude.

    Google Scholar 

  • Koo, B. H., Jung, E. J., Seo, W. S., Song, C. J., Chang, H. K., & Bai, D. S. (2005). The comparison of MMPI and neuropsychological tests according to degree of subjective symptom complaints in patients with traumatic head injury. Journal of Korean Neuropsychiatric Association, 44(6), 743–753.

    Google Scholar 

  • Kwon, S.-M. (1992). Differential roles of dysfunctional attitudes and automatic thoughts in depression: An integrated cognitive model of depression. University of Queensland.

  • Lee, J. M., Kim, D. J., Kim, I. Y., Park, K. S., & Kim, S. I. (2002). Detrended fluctuation analysis of EEG in sleep apnea using MIT/BIH polysomnography data. Computers in Biology and Medicine, 32(1), 37–47.

    PubMed  Article  Google Scholar 

  • Lee, J. M., Kim, D. J., Kim, I. Y., Park, K. S., & Kim, S. I. (2004). Nonlinear-analysis of human sleep EEG using detrended fluctuation analysis. Medical Engineering and Physics, 26(9), 773–776.

    PubMed  Article  Google Scholar 

  • Lee, J. S., & Koo, B. H. (2012). Fractal analysis of EEG upon auditory stimulation during waking and hypnosis in healthy volunteers. International Journal of Clinical and Experimental Hypnosis, 60(3), 266–285.

    PubMed  Article  Google Scholar 

  • Lee, J. S., Spiegel, D., Kim, S. B., Lee, J. H., Kim, S. I., Yang, B. H., et al. (2007a). Fractal analysis of EEG in hypnosis and its relationship with hypnotizability. International Journal of Clinical and Experimental Hypnosis, 55(1), 14–31.

    PubMed  Article  Google Scholar 

  • Lee, J. S., Yang, B. H., Lee, J. H., Choi, J. H., Choi, I. G., & Kim, S. B. (2007b). Detrended fluctuation analysis of resting EEG in depressed outpatients and healthy controls. Clinical Neurophysiology, 118(11), 2489–2496.

    PubMed  Article  Google Scholar 

  • Lee, M., Lee, Y., Park, S., Sohn, C., Jung, Y., Hong, S., et al. (1995). A standardization study of beck depression inventory (I): Korean version (K-BDI): Reliability land factor analysis. Korean Journal Psychopathology, 4, 77–95.

    Google Scholar 

  • Lee, Y. (1991). A study of the reliability and the validity of the BDI, SDS, and MMPI-D scales. Korean Journal of Clinical Psychology, 10, 98–113.

    Google Scholar 

  • Linden, M., Habib, T., & Radojevic, V. (1996). A controlled study of the effects of EEG biofeedback on cognition and behavior of children with attention deficit disorder and learning disabilities. Biofeedback and Self-Regulation, 21(1), 35–49.

    PubMed  Article  Google Scholar 

  • Linkenkaer-Hansen, K., Monto, S., Rytsala, H., Suominen, K., Isometsa, E., & Kahkonen, S. (2005). Breakdown of long-range temporal correlations in theta oscillations in patients with major depressive disorder. Journal of Neuroscience, 25(44), 10131–10137.

    PubMed  Article  Google Scholar 

  • Linkenkaer-Hansen, K., Nikulin, V. V., Palva, J. M., Kaila, K., & Ilmoniemi, R. J. (2004). Stimulus-induced change in long-range temporal correlations and scaling behaviour of sensorimotor oscillations. European Journal of Neuroscience, 19(1), 203–211.

    PubMed  Article  Google Scholar 

  • Lubar, J. F. (1991). Discourse on the development of EEG diagnostics and biofeedback for attention-deficit/hyperactivity disorders. Biofeedback and Self Regulation, 16(3), 201–225.

    PubMed  Article  Google Scholar 

  • Monastra, V. J., Monastra, D. M., & George, S. (2002). The effects of stimulant therapy, EEG biofeedback, and parenting style on the primary symptoms of attention-deficit/hyperactivity disorder. Applied Psychophysiology and Biofeedback, 27(4), 231–249.

    PubMed  Article  Google Scholar 

  • Nikulin, V. V., & Brismar, T. (2004). Long-range temporal correlations in alpha and beta oscillations: Effect of arousal level and test-retest reliability. Clinical Neurophysiology, 115(8), 1896–1908.

    PubMed  Article  Google Scholar 

  • Niv, S. (2013). Clinical efficacy and potential mechanisms of neurofeedback. Personality and Individual Differences, 54(6), 676–686.

    Article  Google Scholar 

  • Park, D.-H., & Shin, C.-J. (2012). Application of detrended fluctuation analysis of electroencephalography during sleep onset period. Korean Journal of Biological Psychiatry. 19(1), 58–62.

  • Peng, C. K., Havlin, S., Stanley, H. E., & Goldberger, A. L. (1995). Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos, 5(1), 82–87.

    PubMed  Article  Google Scholar 

  • Peniston, E. G., & Kulkosky, P. J. (1990). Alcoholic personality and alpha-theta brainwave training. Medical Psychotherapy, 3, 37–55.

    Google Scholar 

  • Peniston, E. G., & Kulkosky, P. J. (1991). Alpha-theta brainwave neurofeedback for Vietnam veterans with combat-related post-traumatic stress disorder. Medical Psychotherapy, 4(1), 47–60.

    Google Scholar 

  • Raymond, J., Varney, C., Parkinson, L. A., & Gruzelier, J. H. (2005). The effects of alpha/theta neurofeedback on personality and mood. Cognitive Brain Research, 23(2), 287–292.

    PubMed  Article  Google Scholar 

  • Rhee, M. (1995). A standardization study of Beck Depression Inventory; Korean version (K-BDI): Validity. Korean Journal Psychopathology, 4, 96–104.

    Google Scholar 

  • Ros, T., Théberge, J., Frewen, P. A., Kluetsch, R., Densmore, M., Calhoun, V. D., et al. (2013). Mind over chatter: Plastic up-regulation of the fMRI salience network directly after EEG neurofeedback. Neuroimage, 65, 324–335.

    PubMed  Article  Google Scholar 

  • Rosenfeld, J. P., Cha, G., Blair, T., & Gotlib, I. H. (1995). Operant (biofeedback) control of left-right frontal alpha power differences: Potential neurotherapy for affective disorders. Biofeedback and Self-Regulation, 20(3), 241–258.

    PubMed  Article  Google Scholar 

  • Rossiter, D. T. R., & La Vaque, T. J. (1995). A comparison of EEG biofeedback and psychostimulants in treating attention deficit/hyperactivity disorders. Journal of Neurotherapy, 1(1), 48–59.

    Article  Google Scholar 

  • Schabus, M., Griessenberger, H., Gnjezda, M. T., Heib, D. P. J., Wislowska, M., & Hoedlmoser, K. (2017). Better than sham? A double-blind placebo-controlled neurofeedback study in primary insomnia. Brain, 140(4), 1041–1052.

    PubMed  PubMed Central  Article  Google Scholar 

  • Schmitz, N., Hartkamp, N., & Franke, G. H. (2000). Assessing clinically significant change: Application to the SCL-90-R. Psychological Reports, 86(1), 263–274.

    PubMed  Article  Google Scholar 

  • Schutze, M. D., & Junghanns, K. (2015). The difficulty of staying awake during alpha/theta neurofeedback training. Applied Psychophysiology and Biofeedback, 40(2), 85–94.

    PubMed  Article  Google Scholar 

  • Sokhadze, T. M., Cannon, R. L., & Trudeau, D. L. (2008). EEG biofeedback as a treatment for substance use disorders: Review, rating of efficacy and recommendations for further research. Journal of Neurotherapy, 12(1), 5–43.

    Article  Google Scholar 

  • Stam, C. J., Montez, T., Jones, B. F., Rombouts, S. A., van der Made, Y., Pijnenburg, Y. A., et al. (2005). Disturbed fluctuations of resting state EEG synchronization in Alzheimer’s disease. Clinical Neurophysiology, 116(3), 708–715.

    PubMed  Article  Google Scholar 

  • Sterman, M. (1977). Sensorimotor EEG operant conditioning: Experimental and clinical effects. The Pavlovian Journal of Biological Science: Official Journal of the Pavlovian, 12(2), 63–92.

    Google Scholar 

  • Sterman, M. B. (1996). Physiological origins and functional correlates of EEG rhythmic activities: Implications for self-regulation. Biofeedback and Self-Regulation, 21(1), 3–33.

    PubMed  Article  Google Scholar 

  • Taneli, B., & Krahne, W. (1987). EEG changes of transcendental meditation practitioners. Advances in Biological Psychiatry, 16, 41–71

    Google Scholar 

  • Tonner, P. H., & Bein, B. (2006). Classic electroencephalographic parameters: Median frequency, spectral edge frequency etc. Best Practice & Research: Clinical Anaesthesiology, 20(1), 147–159.

    Google Scholar 

  • Vaitl, D., Birbaumer, N., Gruzelier, J., Jamieson, G. A., Kotchoubey, B., Kubler, A., et al. (2005). Psychobiology of altered states of consciousness. Psychological Bulletin, 131(1), 98–127.

    PubMed  Article  Google Scholar 

  • Valencia, M., Artieda, J., Alegre, M., & Maza, D. (2008). Influence of filters in the detrended fluctuation analysis of digital electroencephalographic data. Journal of Neuroscience Methods, 170(2), 310–316.

    PubMed  Article  Google Scholar 

  • Woyshville, M. J., & Calabrese, J. R. (1994). Quantification of occipital EEG changes in Alzheimer’s disease utilizing a new metric: The fractal dimension. Biological Psychiatry, 35(6), 381–387.

    PubMed  Article  Google Scholar 

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Acknowledgement

This work was supported by the 2015 Yeungnam University Research Grant.

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Lee, YJ., Kim, HG., Cheon, EJ. et al. The Analysis of Electroencephalography Changes Before and After a Single Neurofeedback Alpha/Theta Training Session in University Students. Appl Psychophysiol Biofeedback 44, 173–184 (2019). https://doi.org/10.1007/s10484-019-09432-4

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Keywords

  • Neurofeedback
  • Alpha/theta
  • Quantitative electroencephalography
  • Meditation