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EPAT: a user-friendly MATLAB toolbox for EEG/ERP data processing and analysis.

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Bibliographic Details
Title: EPAT: a user-friendly MATLAB toolbox for EEG/ERP data processing and analysis.
Authors: Jianwei Shi, Xun Gong, Ziang Song, Wenkai Xie, Yanfeng Yang, Xiangjie Sun, Penghu Wei, Changming Wang, Guoguang Zhao
Source: Frontiers in Neuroinformatics; 2024, p01-13, 13p
Subject Terms: ELECTROENCEPHALOGRAPHY, INDEPENDENT component analysis, GRAPHICAL user interfaces, WILCOXON signed-rank test, DATA analysis, ENTERPRISE resource planning software
Abstract: Background: At the intersection of neural monitoring and decoding, event- related potential (ERP) based on electroencephalography (EEG) has opened a window into intrinsic brain function. The stability of ERP makes it frequently employed in the field of neuroscience. However, project-specific custom code, tracking of user-defined parameters, and the large diversity of commercial tools have limited clinical application. Methods: We introduce an open-source, user-friendly, and reproducible MATLAB toolbox named EPAT that includes a variety of algorithms for EEG data preprocessing. It provides EEGLAB-based template pipelines for advanced multi-processing of EEG, magnetoencephalography, and polysomnogram data. Participants evaluated EEGLAB and EPAT across 14 indicators, with satisfaction ratings analyzed using the Wilcoxon signed-rank test or paired t-test based on distribution normality. Results: EPAT eases EEG signal browsing and preprocessing, EEG power spectrum analysis, independent component analysis, time-frequency analysis, ERP waveform drawing, and topological analysis of scalp voltage. A user-friendly graphical user interface allows clinicians and researchers with no programming background to use EPAT. Conclusion: This article describes the architecture, functionalities, and workflow of the toolbox. The release of EPAT will help advance EEG methodology and its application to clinical translational studies. [ABSTRACT FROM AUTHOR]
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Database: Biomedical Index
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