@article{Zhang2020, 
author = {Libo Zhang and Zhenjiang Li and Fengrui Zhang and Ruolei Gu and Weiwei Peng and Li Hu},
title = {Demystifying signal processing techniques to extract task- related EEG responses for psychologists},
year = {2020},
journal = {Brain Science Advances},
volume = {6},
number = {3},
pages = {171-188},
keywords = {task-related EEG, preprocessing, time domain analysis, time-frequency analysis},
url = {https://www.sciopen.com/article/10.26599/BSA.2020.9050018},
doi = {10.26599/BSA.2020.9050018},
abstract = {To investigate neural mechanisms of human psychology with electroencephalography (EEG), we typically instruct participants to perform certain tasks with simultaneous recording of their brain activities. The identification of task-related EEG responses requires data analysis techniques that are normally different from methods for analyzing resting-state EEG. This review aims to demystify commonly used signal processing methods for identifying task-related EEG activities for psychologists. To achieve this goal, we first highlight the different preprocessing pipelines between task-related EEG and resting-state EEG. We then discuss the methods to extract and visualize event-related potentials in the time domain and event-related oscillatory responses in the time-frequency domain. Potential applications of advanced techniques such as source analysis and single-trial analysis are briefly discussed. We conclude this review with a short summary of task-related EEG data analysis, recommendations for further study, and caveats we should take heed of.}
}