机构：[1]Key Laboratory of Measurement Technology and Instrumentation of Hebei Province, Institute of Electric Engineering, Yanshan University, Qinhuangdao, China,[2]Handan First Central Hospital, Handan, China,[3]Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China神经科系统神经内科首都医科大学宣武医院
The mild cognitive impairment (MCI) stage plays an essential role in preventing the progression of older adults to Alzheimer's disease. In this study, neurofeedback training (NFT) is applied to improve MCI brain cognitive function. To assess the improvement effect, a novel algorithm called Weighted Multiple Multiscale Entropy (WMMSE) is proposed to extract and analyze the electroencephalogram (EEG) features of patients with MCI. To overcome the information loss problem of traditional multiscale entropy (MSE), WMMSE fully considered the correlation of the sequence and the contribution of each sequence to the total entropy. The experimental group composed of 39 patients with MCI was subjected to NFT for 10 days during two sessions. The control group included 21 patients with MCI without any intervention. The Lempel-Ziv complexity (LZC) was used for primary assessment, and WMMSE was used to accurately analyze the effect of NFT. The results show that the WMMSE values of F4, C3, C4, O1, and T5 channels post-NFT are higher compared with pre-NFT and significant differences (P < 0.05). Moreover, the cognitive subscale of the Montreal Cognitive Assessment (MoCA) results shows that the post-NFT score is higher than the pre-NFT in the vast majority of the patients with MCI and significant differences (P < 0.05). When compared with the control group, the WMMSE values of the experimental group increased in each channel. Therefore, the NFT intervention method contributes to brain cognitive functional recovery, and WMMSE can be used as a biomarker to evaluate the state of MCI brain cognitive function.
基金：
This study was supported by the China Postdoctoral Science
Foundation (Grant No. 2014M550582), the Hebei Provincial
Natural Science Foundation China (Grant No. F2019203515),
and the National Natural Science Foundation of China (Grant
No. 61633018 and 82020108013).
第一作者机构：[1]Key Laboratory of Measurement Technology and Instrumentation of Hebei Province, Institute of Electric Engineering, Yanshan University, Qinhuangdao, China,
通讯作者：
推荐引用方式(GB/T 7714)：
Rui Su,Xin Li,Yi Liu,et al.Evaluation of the Brain Function State During Mild Cognitive Impairment Based on Weighted Multiple Multiscale Entropy[J].FRONTIERS IN AGING NEUROSCIENCE.2021,13:doi:10.3389/fnagi.2021.625081.
APA：
Rui Su,Xin Li,Yi Liu,Wei Cui,Ping Xie&Ying Han.(2021).Evaluation of the Brain Function State During Mild Cognitive Impairment Based on Weighted Multiple Multiscale Entropy.FRONTIERS IN AGING NEUROSCIENCE,13,
MLA：
Rui Su,et al."Evaluation of the Brain Function State During Mild Cognitive Impairment Based on Weighted Multiple Multiscale Entropy".FRONTIERS IN AGING NEUROSCIENCE 13.(2021)
