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使用移动、家庭内采集脑电图评估大脑活动的可行性:方法与分析。

Feasibility of assessing brain activity using mobile, in-home collection of electroencephalography: methods and analysis.

机构信息

Department of Biobehavioral Sciences, Teachers College, Columbia University, New York, New York, USA.

Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland, USA.

出版信息

Dev Psychobiol. 2021 Sep;63(6):e22128. doi: 10.1002/dev.22128. Epub 2021 Jun 4.

DOI:10.1002/dev.22128
PMID:34087950
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8478406/
Abstract

The last decade has seen increased availability of mobile electroencephalography (EEG). These mobile systems enable researchers to conduct data collection "in-context," reducing participant burden and potentially increasing diversity and representation of research samples. Our research team completed in-home data collection from more than 400 twelve-month-old infants from low-income backgrounds using a mobile EEG system. In this paper, we provide methodological and analytic guidance for collecting high-quality, mobile EEG in infants. Specifically, we offer insights and recommendations for equipment selection, data collection, and data analysis, highlighting important considerations for selecting a mobile EEG system. Examples include the size of the recording equipment, electrode type, reference types, and available montages. We also highlight important recommendations surrounding preparing a nonstandardized recording environment for EEG collection, obtaining informed consent from parents, instructions for parents during capping and recording, stimuli and task design, training researchers, and monitoring data as it comes in. Additionally, we provide access to the analysis code and demonstrate the robustness of the data from a recent study using this approach, in which 20 artifact-free epochs achieve good internal consistency reliability. Finally, we provide recommendations and publicly available resources for future studies aiming to collect mobile EEG.

摘要

过去十年中,移动脑电图(EEG)的可用性有所增加。这些移动系统使研究人员能够在“情境中”进行数据收集,从而减少参与者的负担,并可能增加研究样本的多样性和代表性。我们的研究团队使用移动 EEG 系统,从 400 多名来自低收入背景的 12 个月大的婴儿中完成了家庭内的数据收集。在本文中,我们为在婴儿中收集高质量的移动 EEG 提供了方法学和分析指导。具体来说,我们提供了有关设备选择、数据收集和数据分析的见解和建议,强调了为移动 EEG 系统选择合适设备的重要考虑因素。示例包括记录设备的大小、电极类型、参考类型和可用的导联。我们还强调了围绕为 EEG 采集准备非标准化记录环境、从父母那里获得知情同意、在帽檐和记录过程中为父母提供说明、刺激和任务设计、培训研究人员以及监控数据等方面的重要建议。此外,我们还提供了分析代码,并展示了使用这种方法的一项近期研究的数据的稳健性,其中 20 个无伪迹的时段实现了良好的内部一致性可靠性。最后,我们为未来旨在收集移动 EEG 的研究提供了建议和公开可用的资源。

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本文引用的文献

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The Maryland analysis of developmental EEG (MADE) pipeline.马里兰州发育脑电图(MADE)分析管道。
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EEG time-frequency dynamics of early cognitive control development.早期认知控制发展的脑电图时频动态
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Modality-level obstacles and initiatives to improve representation in fetal, infant, and toddler neuroimaging research samples.模态层面的障碍以及提高胎儿、婴儿和幼儿神经影像研究样本代表性的举措。
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Oscillatory But Not Aperiodic Frontal Brain Activity Predicts the Development of Executive Control From Infancy to Toddlerhood.振荡而非非周期性额叶脑活动可预测从婴儿期到幼儿期执行控制能力的发展。
Dev Sci. 2025 Mar;28(2):e13613. doi: 10.1111/desc.13613.
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Alzheimer's disease diagnosis using rhythmic power changes and phase differences: a low-density EEG study.利用节律性功率变化和相位差异诊断阿尔茨海默病:一项低密度脑电图研究。
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