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Demystifying signal processing techniques to extract resting-state EEG features for psychologists

摘要Electroencephalography(EEG)is a powerful tool for investigating the brain bases of human psychological processes non-invasively.Some important mental functions could be encoded by resting-state EEG activity;that is,the intrinsic neural activity not elicited by a specific task or stimulus.The extraction of informative features from resting-state EEG requires complex signal processing techniques.This review aims to demystify the widely used resting-state EEG signal processing techniques.To this end,we first offer a preprocessing pipeline and discuss how to apply it to resting-state EEG preprocessing.We then examine in detail spectral,connectivity,and microstate analysis,covering the oft-used EEG measures,practical issues involved,and data visualization.Finally,we briefly touch upon advanced techniques like nonlinear neural dynamics,complex networks,and machine learning.

作者 Zhenjiang Li ^[1] Libo Zhang ^[2] Fengrui Zhang ^[2] Ruolei Gu ^[3] Weiwei Peng ^[4] Li Hu ^[2] 学术成果认领

作者单位 School of Psychology,Jiangxi Normal University,Nanchang 330022,Jiangxi,China ^[1] CAS Key Laboratory of Mental Health,Institute of Psychology,Beijing 100101,China;Department of Psychology,University of Chinese Academy of Sciences,Beijing 100049,China ^[2] Department of Psychology,University of Chinese Academy of Sciences,Beijing 100049,China;CAS Key Laboratory of Behavioral Science,Institute of Psychology,Beijing 100101,China ^[3] College of Psychology and Sociology,Shenzhen University,Shenzhen 518060,China ^[4]

关键词 resting-state EEG preprocessing spectral analysis connectivity analysis microstate analysis

栏目名称

Special Issue on Advances in EEG Technologies

发布时间 2021-12-01（万方平台首次上网日期，不代表论文的发表时间）