8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

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

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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.

          Related collections

          Most cited references25

          • Record: found
          • Abstract: found
          • Article: not found

          EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis

          We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

            This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Brainstorm: A User-Friendly Application for MEG/EEG Analysis

              Brainstorm is a collaborative open-source application dedicated to magnetoencephalography (MEG) and electroencephalography (EEG) data visualization and processing, with an emphasis on cortical source estimation techniques and their integration with anatomical magnetic resonance imaging (MRI) data. The primary objective of the software is to connect MEG/EEG neuroscience investigators with both the best-established and cutting-edge methods through a simple and intuitive graphical user interface (GUI).
                Bookmark

                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/1729512/overviewRole: Role:
                URI : https://loop.frontiersin.org/people/1822331/overviewRole: Role:
                Role: Role:
                Role: Role: Role:
                URI : https://loop.frontiersin.org/people/2323342/overviewRole: Role: Role: Role:
                Role: Role: Role: Role:
                Role: Role: Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/283165/overviewRole: Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/594311/overviewRole: Role: Role: Role: Role: Role:
                Journal
                Front Neuroinform
                Front Neuroinform
                Front. Neuroinform.
                Frontiers in Neuroinformatics
                Frontiers Media S.A.
                1662-5196
                15 May 2024
                2024
                : 18
                : 1384250
                Affiliations
                [1] 1Department of Neurosurgery, Xuanwu Hospital, Capital Medical University , Beijing, China
                [2] 2China International Neuroscience Institute , Beijing, China
                [3] 3School of Psychology and Mental Health, North China University of Science and Technology , Tangshan, China
                Author notes

                Edited by: Ludovico Minati, University of Electronic Science and Technology of China, China

                Reviewed by: Jiu Chen, Nanjing University, China

                Makoto Miyakoshi, Cincinnati Children's Hospital Medical Center, United States

                *Correspondence: Guoguang Zhao, ggzhao@ 123456vip.sina.com
                Changming Wang, superwcm@ 123456163.com

                These authors have contributed equally to this work and share first authorship

                Article
                10.3389/fninf.2024.1384250
                11133744
                38812743
                ce2df8fa-6833-4291-b78d-5c525d27e604
                Copyright © 2024 Shi, Gong, Song, Xie, Yang, Sun, Wei, Wang and Zhao.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 09 February 2024
                : 18 April 2024
                Page count
                Figures: 9, Tables: 2, Equations: 0, References: 25, Pages: 13, Words: 8473
                Funding
                The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Our work is supported by the National Natural Science Foundation of China (62271331; 82030037), the National Natural Science Foundation of Beijing (z220015), the Research Program for the Development of Health of Capital Beijing (2022-2Z-20112), and the Translational and Application Project of Brain inspired and Network Neuroscience on Brain Disorders (11000023T000002036286).
                Categories
                Neuroscience
                Original Research

                Neurosciences
                data processing,electrophysiology,electroencephalography,event-related potential,open source,user-friendly,matlab,toolbox

                Comments

                Comment on this article