EEG Neurofeedback for Working Memory Enhancement: A Literature Review

Zhou Wenbin; Nan Wenya; Fu Yunfa

doi:10.16719/j.cnki.1671-6981.20240301

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Journal of Psychological Science ›› 2024, Vol. 47 ›› Issue (3) : 514-521. DOI: 10.16719/j.cnki.1671-6981.20240301

General Psychology，Experimental Psychology & Ergonomics

EEG Neurofeedback for Working Memory Enhancement: A Literature Review

Zhou Wenbin¹, Nan Wenya¹, Fu Yunfa²

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Abstract

Working memory refers to the ability to maintain and manipulate information over a period of seconds. In daily life, many complex cognitive activities such as learning and decision-making need the participation of working memory. Whether working memory performance can be improved by certain ways of training has been a hot research topic.
Neurofeedback (NF) is a type of biofeedback that uses the principle of operational conditioning to enable individuals to learn regulating their own brain activity. During electroencephalogram (EEG) NF training, the EEG signals are recorded from single or multiple electrodes attached on the scalp and relevant features are extracted and presented to the training individuals in real time by visual, auditory, or combined visual-auditory forms. Thus, participants can be aware of their brain state in real time. When their brain activity meets some predefined rewarded criteria, they will be rewarded by the feedback interface that presents real time feedback feature, such as increasing the sphere size in visual feedback, music quality in auditory feedback, etc. With NF training practice, they will learn how to adjust their brain activities that underlie a specific behavior or pathology.
A large amount of studies have shown that NF training can improve cognitive ability and behavioral performance in both clinical patients and healthy population. Regarding the NF training effectiveness for working memory enhancement, the existing research conclusions are not consistent due to the variations of the experimental design, training protocol, participants’ population, and sample size in the literature. Therefore, this study systematically reviewed previous studies on EEG NF training for working memory performance improvement. It started with the principle and mechanism of NF training and the introduction of the current research progress. Then the article reviewed the experimental results using different NF training protocols including theta enhancement NF, alpha enhancement NF, SMR enhancement NF, beta enhancement NF, gamma enhancement NF and two frequency bands NF protocols. We found that alpha, SMR and theta enhancement NF have shown the benefits on working memory enhancement in most studies. However, a few studies have reported inconsistent results, including the failure to adjust the training EEG feature (i.e. the non-learner problem) and no significant enhancement in working memory compared to the control group.
Future research can be conducted from following three aspects. First, the neural mechanism of EEG NF training effects on working memory has not been clear yet. Previous work only examined the EEG activity during NF training and resting periods. Whether and how NF training influences the brain activity in working memory task and results in working memory performance change remains unknown yet. Future work can utilize a variety of imaging methods such as EEG, functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS) and positron emission tomography (PET) to examine the brain activities during NF training, during resting state and during working memory task. Second, the non-learner problem has been reported in a number of studies. Although a few studies have identified some physiological and psychological predictors for non-learners in some NF protocols, the findings cannot be generalized due to the complexity of EEG activity, the variety of participants’ population and inconsistent experimental design. Future work is suggested to utilize machine learning methods to identify the predictors of non-learners in different NF training protocols in order to understand the reason of non-learner problem, and save time and effort on non-learners. Finally, the optimization of training parameters including training schedule and feedback interface, the adoption of randomized double-blind sham-controlled experimental design, clear reporting the experimental methods and results are desired in future NF studies. This review is expected to provide reference and pave the way for future research.

Key words

neurofeedback / EEG / working memory

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Zhou Wenbin, Nan Wenya, Fu Yunfa. EEG Neurofeedback for Working Memory Enhancement: A Literature Review[J]. Journal of Psychological Science. 2024, 47(3): 514-521 https://doi.org/10.16719/j.cnki.1671-6981.20240301

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