ArticleFrontiers in neuroinformatics2024
EPAT: a user-friendly MATLAB toolbox for EEG/ERP data processing and analysis.
Article in Frontiers in neuroinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- YOLOBT: a novel ERP bad trial detection network dynamically adjusting based on global signal quality.Frontiers in human neuroscience · 2026Article
- Schizophrenia recognition based on three-dimensional adaptive graph convolutional neural network.Scientific reports · 2025Article
- Altered N170 and compensatory mechanisms in face processing in schizophrenia: an event-related potential study.Frontiers in psychiatry · 2025Article
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Authors and funding
9 authors.
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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.
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Registered trials
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