Department of Physiological Psychology, University of Salzburg, Hellbrunnerstrasse 34, Salzburg, Austria.
Appl Psychophysiol Biofeedback. 2011 Mar;36(1):37-45. doi: 10.1007/s10484-010-9142-x.
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.
神经反馈(NF)是一种已被证明对治疗各种疾病(如癫痫或注意力缺陷障碍(ADHD))有效的工具。根据各自的应用,参与者可能需要进行大量的训练课程,才能按照指示自愿调节脑电图(EEG)节律。此外,尽管进行了多次训练课程,但许多人仍然无法学习到这一点。因此,我们有兴趣确定在早期训练课程中的表现是否可以用来预测参与者是否会学会调节 EEG 节律。在这里,我们提出了一种简单易用但准确的方法来预测个别参与者的表现。我们使用了一组感觉运动节律(SMR 12-15 Hz)NF 训练课程(实验 1)来预测另一项研究(实验 2)中参与者的表现。然后,我们使用在实验 2 中获得的数据来预测实验 1 中参与者的表现。我们正确预测了第一组 13 名参与者中的 12 名和第二组 14 名参与者的表现;然而,我们无法在第十一次训练课程结束之前做出这些预测。