"Demystifying signal processing techniques to extract resting- state EE" by Zhenjiang Li, Libo Zhang et al.

Article Title

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

Authors

Zhenjiang Li, School of Psychology, Jiangxi Normal University, Nanchang 330022, Jiangxi, China
Libo Zhang, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, China;Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
Fengrui Zhang, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, China;Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
Ruolei Gu, Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China;CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China
Weiwei Peng, College of Psychology and Sociology, Shenzhen University, Shenzhen 518060, China
Li Hu, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, China;Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China

Keywords

resting-state EEG, preprocessing, spectral analysis, connectivity analysis, microstate analysis

Abstract

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.

DOI

https://doi.org/10.26599/BSA.2020.9050019

Publisher

Tsinghua University Press

Recommended Citation

Zhenjiang Li, Libo Zhang, Fengrui Zhang, Ruolei Gu, Weiwei Peng, Li Hu. Demystifying signal processing techniques to extract resting- state EEG features for psychologists. Brain Science Advances 2020, 6(3): 189-209.

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