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

Autor: Jianwei Shi, Xun Gong, Ziang Song, Wenkai Xie, Yanfeng Yang, Xiangjie Sun, Penghu Wei, Changming Wang, Guoguang Zhao
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Frontiers in Neuroinformatics, Vol 18 (2024)
Druh dokumentu: article
ISSN: 1662-5196
DOI: 10.3389/fninf.2024.1384250
Popis: BackgroundAt 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.MethodsWe 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.ResultsEPAT 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.ConclusionThis 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.
Databáze: Directory of Open Access Journals