The Maryland analysis of developmental EEG (MADE) pipeline
The Maryland analysis of developmental EEG (MADE) pipeline
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DOI：
10.1111/psyp.13580
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发表时间：
2020-04-15
期刊：
影响因子：
3.7
通讯作者：
Fox, Nathan A.
中科院分区：
文献类型：
--
作者：
Debnath, Ranjan;Buzzell, George A.;Fox, Nathan A.
与成人EEG相比，从儿科人群记录的EEG信号具有更短的记录周期并且包含更多的伪影污染。因此，儿科EEG数据需要特定的预处理方法，以便在不丢失大量数据的情况下去除环境噪声和生理伪影。然而，目前缺乏适用于儿科EEG的标准自动预处理管道。为了实现EEG预处理的更大标准化，特别是对于儿科数据的分析，我们开发了马里兰州发育EEG分析（MADE）管道，作为与不同硬件系统、不同人群、伪影污染水平和记录长度记录的EEG数据兼容的自动预处理管道。MADE使用EEGLAB和一些EEGLAB插件的功能，并包括额外的定制功能，特别适用于从儿科人群收集的EEG数据。MADE通过一系列预处理步骤从原始数据文件中处理事件相关和静息状态EEG，并输出经过处理的干净数据，准备在时间，频率或时频域中进行分析。MADE在预处理结束时提供一个报告文件，该文件描述了处理后数据的各种特征，以便于评估处理后数据的质量。在这篇文章中，我们讨论了一些实际问题，这是具体相关的小儿脑电预处理。我们还提供定制脚本来解决这些实际问题。MADE是根据GNU通用公共许可证的条款免费提供的。
Compared to adult EEG, EEG signals recorded from pediatric populations have shorter recording periods and contain more artifact contamination. Therefore, pediatric EEG data necessitate specific preprocessing approaches in order to remove environmental noise and physiological artifacts without losing large amounts of data. However, there is presently a scarcity of standard automated preprocessing pipelines suitable for pediatric EEG. In an effort to achieve greater standardization of EEG preprocessing, and in particular, for the analysis of pediatric data, we developed the Maryland analysis of developmental EEG (MADE) pipeline as an automated preprocessing pipeline compatible with EEG data recorded with different hardware systems, different populations, levels of artifact contamination, and length of recordings. MADE uses EEGLAB and functions from some EEGLAB plugins and includes additional customized features particularly useful for EEG data collected from pediatric populations. MADE processes event-related and resting state EEG from raw data files through a series of preprocessing steps and outputs processed clean data ready to be analyzed in time, frequency, or time-frequency domain. MADE provides a report file at the end of the preprocessing that describes a variety of features of the processed data to facilitate the assessment of the quality of processed data. In this article, we discuss some practical issues, which are specifically relevant to pediatric EEG preprocessing. We also provide custom-written scripts to address these practical issues. MADE is freely available under the terms of the GNU General Public License at .