resting-state EEG, preprocessing, spectral analysis, connectivity analysis, microstate analysis
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.
Tsinghua University Press
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.