连续婴儿脑电图微状态分析:教程与可靠性。

IF 2.3 3区 医学 Q3 CLINICAL NEUROLOGY
Brain Topography Pub Date : 2024-07-01 Epub Date: 2024-03-02 DOI:10.1007/s10548-024-01043-5
Armen Bagdasarov, Denis Brunet, Christoph M Michel, Michael S Gaffrey
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引用次数: 0

摘要

静息态脑电图的微状态分析是一种独特的数据驱动方法,用于识别头皮电位拓扑图或微状态的模式,这些模式反映了随时间动态演变的稳定但短暂的同步神经活动。婴儿期是大脑快速发育和可塑性的关键时期,微状态分析为描述大脑活动的空间和时间动态提供了独特的机会。然而,这种方法得出的测量结果(如时间属性、过渡概率、神经源)在婴儿期是否表现出很强的心理测量属性(即可靠性)尚不清楚,而这是我们了解微状态如何由早期生活经历形成以及它们是否与婴儿能力的个体差异有关的关键信息。由于缺乏对婴儿脑电图进行微状态分析的方法资源,这进一步阻碍了婴儿研究人员采用这一前沿方法。因此,在本研究中,我们系统地解决了这些知识空白,并报告了除过渡概率外,大多数基于微状态的大脑组织和功能测量结果在观看四分钟静息状态视频数据的情况下是稳定的,并且在仅一分钟的情况下具有高度的内部一致性。除了这些结果,我们还提供了使用免费、用户友好的软件 Cartool 进行微状态分析的分步教程、配套网站和开放获取的数据。总之,目前的研究证明了利用脑电图微状态分析研究婴儿大脑发育的可靠性和可行性,并提高了这种方法在发育神经科学领域的可及性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Microstate Analysis of Continuous Infant EEG: Tutorial and Reliability.

Microstate Analysis of Continuous Infant EEG: Tutorial and Reliability.

Microstate analysis of resting-state EEG is a unique data-driven method for identifying patterns of scalp potential topographies, or microstates, that reflect stable but transient periods of synchronized neural activity evolving dynamically over time. During infancy - a critical period of rapid brain development and plasticity - microstate analysis offers a unique opportunity for characterizing the spatial and temporal dynamics of brain activity. However, whether measurements derived from this approach (e.g., temporal properties, transition probabilities, neural sources) show strong psychometric properties (i.e., reliability) during infancy is unknown and key information for advancing our understanding of how microstates are shaped by early life experiences and whether they relate to individual differences in infant abilities. A lack of methodological resources for performing microstate analysis of infant EEG has further hindered adoption of this cutting-edge approach by infant researchers. As a result, in the current study, we systematically addressed these knowledge gaps and report that most microstate-based measurements of brain organization and functioning except for transition probabilities were stable with four minutes of video-watching resting-state data and highly internally consistent with just one minute. In addition to these results, we provide a step-by-step tutorial, accompanying website, and open-access data for performing microstate analysis using a free, user-friendly software called Cartool. Taken together, the current study supports the reliability and feasibility of using EEG microstate analysis to study infant brain development and increases the accessibility of this approach for the field of developmental neuroscience.

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来源期刊
Brain Topography
Brain Topography 医学-临床神经学
CiteScore
4.70
自引率
7.40%
发文量
41
审稿时长
3 months
期刊介绍: Brain Topography publishes clinical and basic research on cognitive neuroscience and functional neurophysiology using the full range of imaging techniques including EEG, MEG, fMRI, TMS, diffusion imaging, spectroscopy, intracranial recordings, lesion studies, and related methods. Submissions combining multiple techniques are particularly encouraged, as well as reports of new and innovative methodologies.
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