Abstract：
BACKGROUND: High-density electroencephalography (hdEEG) is a technique used for the characterization of the neural activity and connectivity in the human brain. The analysis of EEG data involves several steps, including signal pre-processing, head modelling, source localization and activity/connectivity quantification. Visual check of the analysis steps is often necessary, making the process time- and resource-consuming and, therefore, not feasible for large datasets.
RESULTS: Here we present the Noninvasive Electrophysiology Toolbox (NET), an open-source software for large-scale analysis of hdEEG data, running on the cross-platform MATLAB environment. NET combines all the tools required for a complete hdEEG analysis workflow, from raw signals to final measured values. By relying on reconstructed neural signals in the brain, NET can perform traditional analyses of time-locked neural responses, as well as more advanced functional connectivity and brain mapping analyses. The extracted quantitative neural data can be exported to provide broad compatibility with other software.
CONCLUSIONS: NET is freely available (https://github.com/bind-group-kul/net) under the GNU public license for non-commercial use and open-source development, together with a graphical user interface (GUI) and a user tutorial. While NET can be used interactively with the GUI, it is primarily aimed at unsupervised automation to process large hdEEG datasets efficiently. Its implementation creates indeed a highly customizable program suitable for analysis automation and tight integration into existing workflows.
RESULTS: Here we present the Noninvasive Electrophysiology Toolbox (NET), an open-source software for large-scale analysis of hdEEG data, running on the cross-platform MATLAB environment. NET combines all the tools required for a complete hdEEG analysis workflow, from raw signals to final measured values. By relying on reconstructed neural signals in the brain, NET can perform traditional analyses of time-locked neural responses, as well as more advanced functional connectivity and brain mapping analyses. The extracted quantitative neural data can be exported to provide broad compatibility with other software.
CONCLUSIONS: NET is freely available (https://github.com/bind-group-kul/net) under the GNU public license for non-commercial use and open-source development, together with a graphical user interface (GUI) and a user tutorial. While NET can be used interactively with the GUI, it is primarily aimed at unsupervised automation to process large hdEEG datasets efficiently. Its implementation creates indeed a highly customizable program suitable for analysis automation and tight integration into existing workflows.
摘要：
背景：高密度脑电图（hdEEG）是一种用于表征人脑中神经活动和连通性的技术。脑电图数据的分析涉及几个步骤,包括信号预处理，头部造型,源定位和活动/连通性量化。通常需要对分析步骤进行目视检查，使过程耗时和消耗资源，因此,对于大型数据集来说是不可行的。
结果：这里我们介绍了非侵入性电生理工具箱（NET），用于大规模分析hdEEG数据的开源软件，在跨平台MATLAB环境中运行。NET结合了完整的HDEEG分析工作流程所需的所有工具，从原始信号到最终测量值。依靠大脑中重建的神经信号，NET可以对时间锁定的神经反应进行传统分析，以及更先进的功能连接和大脑映射分析。可以导出提取的定量神经数据以提供与其他软件的广泛兼容性。
结论：NET在GNU公共许可证下免费提供（https://github.com/bind-group-kul/net），用于非商业用途和开源开发，以及图形用户界面(GUI)和用户教程。NET可以与GUI交互使用，它主要针对无监督的自动化，以有效地处理大型hdEEG数据集。它的实施确实创建了一个高度可定制的程序，适用于分析自动化和与现有工作流程的紧密集成。
结果：这里我们介绍了非侵入性电生理工具箱（NET），用于大规模分析hdEEG数据的开源软件，在跨平台MATLAB环境中运行。NET结合了完整的HDEEG分析工作流程所需的所有工具，从原始信号到最终测量值。依靠大脑中重建的神经信号，NET可以对时间锁定的神经反应进行传统分析，以及更先进的功能连接和大脑映射分析。可以导出提取的定量神经数据以提供与其他软件的广泛兼容性。
结论：NET在GNU公共许可证下免费提供（https://github.com/bind-group-kul/net），用于非商业用途和开源开发，以及图形用户界面(GUI)和用户教程。NET可以与GUI交互使用，它主要针对无监督的自动化，以有效地处理大型hdEEG数据集。它的实施确实创建了一个高度可定制的程序，适用于分析自动化和与现有工作流程的紧密集成。
