Predicting Successful Learning of SMR Neurofeedback in Healthy Participants: Methodological Considerations

Neurofeedback (NF) is a tool that has proven helpful in the treatment of various disorders such as epilepsy or attention deficit disorder (ADHD). Depending on the respective application, a high number of training sessions might be necessary before participants can voluntarily modulate the electroenc...

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Bibliographic Details
Published in:Applied psychophysiology and biofeedback 2011-03, Vol.36 (1), p.37-45
Main Authors: Weber, E., Köberl, A., Frank, S., Doppelmayr, M.
Format: Article
Language:English
Subjects:
Adult
Analysis
Attention-deficit hyperactivity disorder
Behavioral Science and Psychology
Biofeedback
Biofeedback training
Data Interpretation, Statistical
Electroencephalography
Epilepsy
Experiments
Female
Health Psychology
Humans
Learning
Male
Medical research
Motor Skills
Neurofeedback - methods
Psychology
Psychomotor Performance - physiology
Psychotherapy and Counseling
Public Health
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Summary:Neurofeedback (NF) is a tool that has proven helpful in the treatment of various disorders such as epilepsy or attention deficit disorder (ADHD). Depending on the respective application, a high number of training sessions might be necessary before participants can voluntarily modulate the electroencephalographic (EEG) rhythms as instructed. In addition, many individuals never learn to do so despite numerous training sessions. Thus, we are interested in determining whether or not performance during the early training sessions can be used to predict if a participant will learn to regulate the EEG rhythms. Here, we propose an easy to use, but accurate method for predicting the performance of individual participants. We used a sample set of sensorimotor rhythm (SMR 12–15 Hz) NF training sessions (experiment 1) to predict the performance of the participants of another study (experiment 2). We then used the data obtained in experiment 2 to predict the performance of participants in experiment 1. We correctly predicted the performance of 12 out of 13 participants in the first group and all 14 participants in the second group; however, we were not able to make these predictions before the end of the eleventh training session.
ISSN:1090-0586
1573-3270
DOI:10.1007/s10484-010-9142-x