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

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Názov: EPAT: a user-friendly MATLAB toolbox for EEG/ERP data processing and analysis.
Autori: Jianwei Shi, Xun Gong, Ziang Song, Wenkai Xie, Yanfeng Yang, Xiangjie Sun, Penghu Wei, Changming Wang, Guoguang Zhao
Zdroj: Frontiers in Neuroinformatics; 2024, p01-13, 13p
Predmety: ELECTROENCEPHALOGRAPHY, INDEPENDENT component analysis, GRAPHICAL user interfaces, WILCOXON signed-rank test, DATA analysis, ENTERPRISE resource planning software
Abstrakt: 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]
Copyright of Frontiers in Neuroinformatics is the property of Frontiers Media S.A. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Label: Title
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  Data: EPAT: a user-friendly MATLAB toolbox for EEG/ERP data processing and analysis.
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  Data: <searchLink fieldCode="AR" term="%22Jianwei+Shi%22">Jianwei Shi</searchLink><br /><searchLink fieldCode="AR" term="%22Xun+Gong%22">Xun Gong</searchLink><br /><searchLink fieldCode="AR" term="%22Ziang+Song%22">Ziang Song</searchLink><br /><searchLink fieldCode="AR" term="%22Wenkai+Xie%22">Wenkai Xie</searchLink><br /><searchLink fieldCode="AR" term="%22Yanfeng+Yang%22">Yanfeng Yang</searchLink><br /><searchLink fieldCode="AR" term="%22Xiangjie+Sun%22">Xiangjie Sun</searchLink><br /><searchLink fieldCode="AR" term="%22Penghu+Wei%22">Penghu Wei</searchLink><br /><searchLink fieldCode="AR" term="%22Changming+Wang%22">Changming Wang</searchLink><br /><searchLink fieldCode="AR" term="%22Guoguang+Zhao%22">Guoguang Zhao</searchLink>
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  Data: Frontiers in Neuroinformatics; 2024, p01-13, 13p
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  Data: <searchLink fieldCode="DE" term="%22ELECTROENCEPHALOGRAPHY%22">ELECTROENCEPHALOGRAPHY</searchLink><br /><searchLink fieldCode="DE" term="%22INDEPENDENT+component+analysis%22">INDEPENDENT component analysis</searchLink><br /><searchLink fieldCode="DE" term="%22GRAPHICAL+user+interfaces%22">GRAPHICAL user interfaces</searchLink><br /><searchLink fieldCode="DE" term="%22WILCOXON+signed-rank+test%22">WILCOXON signed-rank test</searchLink><br /><searchLink fieldCode="DE" term="%22DATA+analysis%22">DATA analysis</searchLink><br /><searchLink fieldCode="DE" term="%22ENTERPRISE+resource+planning+software%22">ENTERPRISE resource planning software</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Frontiers in Neuroinformatics is the property of Frontiers Media S.A. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3389/fninf.2024.1384250
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              Text: 2024
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