Volume 11, Issue 5 (September & October - Special Issue on Cognitive Neuroscience 2020)
BCN 2020, 11(5): 701-714 |
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Khodakarami Z, Firoozabadi M. Psychological, Neurophysiological, and Mental Factors Associated With Gamma-Enhancing Neurofeedback Success. BCN 2020; 11 (5) :701-714
URL: http://bcn.iums.ac.ir/article-1-1511-en.html
URL: http://bcn.iums.ac.ir/article-1-1511-en.html
1- Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2- Department of Medical Physics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
2- Department of Medical Physics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
Abstract:
Introduction: Regarding the neurofeedback training process, previous studies indicate that 10%-50% of subjects cannot gain control over their brain activity even after repeated training sessions. This study is conducted to overcome this problem by investigating inter-individual differences in neurofeedback learning to propose some predictors for the trainability of subjects.
Methods: Eight healthy female students took part in 8 (electroencephalography) EEG neurofeedback training sessions for enhancing EEG gamma power at the Oz channel. We studied participants’ preexisting fluid intelligence and EEG frequency sub-bands’ power during 2-min eyes-closed rest and a cognitive task as psychological and neurophysiological factors, concerning neurofeedback learning performance. We also assessed the self-reports of participants about mental strategies used by them during neurofeedback to identify the most effective successful strategies.
Results: The results revealed that a significant percentage of individuals (25% in this study) cannot learn how to control their brain gamma activity using neurofeedback. Our findings suggest that fluid intelligence, gamma power during a cognitive task, and alpha power at rest can predict gamma-enhancing neurofeedback performance of individuals. Based on our study, neurofeedback learning is a form of implicit learning. We also found that learning without a user’s mental efforts to find out successful mental strategies, in other words, unconscious learning, lead to more success in gamma-enhancing neurofeedback.
Conclusion: Our results may improve gamma neurofeedback efficacy for further clinical usage and studies by giving insight about both non-trainable individuals and effective mental strategies.
Methods: Eight healthy female students took part in 8 (electroencephalography) EEG neurofeedback training sessions for enhancing EEG gamma power at the Oz channel. We studied participants’ preexisting fluid intelligence and EEG frequency sub-bands’ power during 2-min eyes-closed rest and a cognitive task as psychological and neurophysiological factors, concerning neurofeedback learning performance. We also assessed the self-reports of participants about mental strategies used by them during neurofeedback to identify the most effective successful strategies.
Results: The results revealed that a significant percentage of individuals (25% in this study) cannot learn how to control their brain gamma activity using neurofeedback. Our findings suggest that fluid intelligence, gamma power during a cognitive task, and alpha power at rest can predict gamma-enhancing neurofeedback performance of individuals. Based on our study, neurofeedback learning is a form of implicit learning. We also found that learning without a user’s mental efforts to find out successful mental strategies, in other words, unconscious learning, lead to more success in gamma-enhancing neurofeedback.
Conclusion: Our results may improve gamma neurofeedback efficacy for further clinical usage and studies by giving insight about both non-trainable individuals and effective mental strategies.
Keywords: Neurofeedback, Brain-Computer Interface (BCI)-illiteracy, Performance prediction, Fluid intelligence, Mental strategies
Type of Study: Original |
Subject:
Clinical Neuroscience
Received: 2019/05/27 | Accepted: 2020/10/2 | Published: 2020/09/1
Received: 2019/05/27 | Accepted: 2020/10/2 | Published: 2020/09/1
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