Background

Most commonly used neurofeedback training (NFT) methods are able to assist subjects towards an increase/decrease in EEG features. So, it is possible that the enhancement/inhabitation in a subject’s EEG features exceed normal limits if the process of changes in brain activity in the subject is very successful. This issue may also bring about a reduction in the effectiveness of NFT.

New method

A soft boundary-based NFT method was proposed for learning how to control the EEG features during training. According to this method, an initial group was defined within which the training features of subjects’ EEG signals were placed prior to training and a target group was considered referring to what the features of the EEG signals should be shifted towards during training. In the course of training, the fuzzy similarity of EEG features of subject towards the target group center was measured and the subject’s score was increased if their fuzzy similarity was higher than a threshold. Within this method, an adaptive scoring index (the scores assigned to subjects for each achievement) was defined whose value was determined according to brain activity of the subject.

Results

Increase/decrease in large amounts in the training features of subject’s EEG could lead to a descending trend in the scores received using the proposed method.

Comparison with existing methods

The proposed method may assist subjects to control their EEG signal features within the target group range.

Conclusion

The proposed method may be able to prevent the side effects of neurofeedback.

中文翻译：

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基于模糊相似性度量的基于软边界的神经反馈训练：一种在神经反馈训练过程中学习如何控制脑电信号特征的方法。

背景

最常用的神经反馈训练（NFT）方法能够协助受试者增加/减少脑电图特征。因此，如果受试者大脑活动的变化过程非常成功，则受试者脑电图特征的增强/居住可能超过正常极限。此问题也可能导致NFT的有效性降低。

新方法

提出了一种基于软边界的NFT方法，用于学习训练过程中如何控制脑电特征。根据这种方法，定义了一个初始组，在训练之前将受试者的脑电信号的训练特征放置在其中，并考虑到在训练过程中应将脑电信号的特征转向哪些目标组。在训练过程中，测量受试者的脑电特征与目标群中心的模糊相似性，如果受试者的模糊相似度高于阈值，则得分会增加。在这种方法中，定义了一个自适应评分指数（为每个成就分配给受试者的分数），其值是根据受试者的大脑活动确定的。

结果

大量增加/减少对象的脑电图训练特征可能导致使用所提出的方法获得的分数下降趋势。

与现有方法的比较

所提出的方法可以帮助对象将他们的EEG信号特征控制在目标群体范围内。

结论

所提出的方法可能能够防止神经反馈的副作用。