■在神经监测和解码的交叉点,基于脑电图(EEG)的事件相关电位(ERP)为内在脑功能打开了一个窗口。ERP的稳定性使其在神经科学领域得到了广泛的应用。然而,特定于项目的自定义代码,跟踪用户定义的参数,商业工具的多样性限制了临床应用。
■我们介绍一个开源的,用户友好,和可重复的MATLAB工具箱称为EPAT,包括各种算法的脑电图数据预处理。它提供了基于EEGLAB的模板管道,用于对EEG进行高级多处理,脑磁图,和多导睡眠图数据。参与者评估了EEGLAB和EPAT的14个指标,满意度评分使用Wilcoxon符号秩检验或基于分布正态的配对t检验进行分析。
■EPAT简化了EEG信号浏览和预处理,脑电功率谱分析,独立成分分析,时频分析,ERP波形图,和头皮电压的拓扑分析。用户友好的图形用户界面允许没有编程背景的临床医生和研究人员使用EPAT。
■本文介绍的体系结构,功能,和工具箱的工作流程。EPAT的发布将有助于推进脑电图方法学及其在临床转化研究中的应用。
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.