MEG 微状态:对潜在脑源和潜在神经生理过程的研究。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-11-01 Epub Date: 2024-08-08 DOI:10.1007/s10548-024-01073-z
Christian Valt, Angelantonio Tavella, Cristina Berchio, Dylan Seebold, Leonardo Sportelli, Antonio Rampino, Dean F Salisbury, Alessandro Bertolino, Giulio Pergola
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引用次数: 0

摘要

微状态是通过脑电图(EEG)测量到的大脑活动的瞬时头皮构型。在脑磁图(MEG)数据中应用微状态分析仍具有挑战性。在一个脑磁图数据集(N = 113)中,我们旨在识别静息状态下的脑磁图微态,探索其大脑来源,并将其与睁眼(ROE)或闭眼静息状态(RCE)和听觉错配负性(MMN)任务中的大脑活动变化联系起来。在另一个同时记录 EEG-MEG 数据的数据集中(N = 21),我们研究了 MEG 和 EEG 微状态之间的关联。六个 MEG 微状态(mMS)提供了静息态活动的最佳聚类,每个微状态都与不同的脑源相关联:mMS 1-2:左/右枕顶叶;mMS 3:前颞叶;mMS 4:中央-内侧;mMS 5-6:左/右前顶叶。相对于 ROE,RCE 枕叶α功率的增加与 mMS 1-2 时间覆盖范围的扩大相关(τbs < 0.20,ps > .002),而 MMN 偏差检测的侧化与 mMS 5-6 时间覆盖范围相关(τbs < 0.16,ps > .012)。尽管 mMS 2-3 和 EEG 微状态 B-C 之间存在一些脑源重叠和全局解释方差(rs > 0.60,ps
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MEG Microstates: An Investigation of Underlying Brain Sources and Potential Neurophysiological Processes.

Microstates are transient scalp configurations of brain activity measured by electroencephalography (EEG). The application of microstate analysis in magnetoencephalography (MEG) data remains challenging. In one MEG dataset (N = 113), we aimed to identify MEG microstates at rest, explore their brain sources, and relate them to changes in brain activity during open-eyes (ROE) or closed-eyes resting state (RCE) and an auditory Mismatch Negativity (MMN) task. In another dataset of simultaneously recorded EEG-MEG data (N = 21), we investigated the association between MEG and EEG microstates. Six MEG microstates (mMS) provided the best clustering of resting-state activity, each linked to different brain sources: mMS 1-2: left/right occipito-parietal; mMS 3: fronto-temporal; mMS 4: centro-medial; mMS 5-6: left/right fronto-parietal. Increases in occipital alpha power in RCE relative to ROE correlated with greater mMS 1-2 time coverage (τbs < 0.20, ps > .002), while the lateralization of deviance detection in MMN was associated with mMS 5-6 time coverage (τbs < 0.16, ps > .012). No temporal correlation was found between EEG and MEG microstates (ps > .05), despite some overlap in brain sources and global explained variance between mMS 2-3 and EEG microstates B-C (rs > 0.60, ps < .002). Hence, the MEG signal can be decomposed into microstates, but mMS brain activity clustering captures phenomena different from EEG microstates. Source reconstruction and task-related modulations link mMS to large-scale networks and localized activities. Thus, mMSs offer insights into brain dynamics and task-specific processes, complementing EEG microstates in studying physiological and dysfunctional brain activity.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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