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采用微状态分析技术对 REM 和 NREM 睡眠状态下新生儿大脑的功能动力学进行特征描述。

Characterization of the Functional Dynamics in the Neonatal Brain during REM and NREM Sleep States by means of Microstate Analysis.

机构信息

Department of Neuroscience, Imaging and Clinical Sciences, University "Gabriele d'Annunzio" of Chieti-Pescara, Chieti, Italy.

Behavioral Imaging and Neural Dynamics Center, University "Gabriele d'Annunzio" of Chieti-Pescara, Chieti, Italy.

出版信息

Brain Topogr. 2021 Sep;34(5):555-567. doi: 10.1007/s10548-021-00861-1. Epub 2021 Jul 13.

Abstract

Neonates spend most of their life sleeping. During sleep, their brain experiences fast changes in its functional organization. Microstate analysis permits to capture the rapid dynamical changes occurring in the functional organization of the brain by representing the changing spatio-temporal features of the electroencephalogram (EEG) as a sequence of short-lasting scalp topographies-the microstates. In this study, we modeled the ongoing neonatal EEG into sequences of a limited number of microstates and investigated whether the extracted microstate features are altered in REM and NREM sleep (usually known as active and quiet sleep states-AS and QS-in the newborn) and depend on the EEG frequency band. 19-channel EEG recordings from 60 full-term healthy infants were analyzed using a modified version of the k-means clustering algorithm. The results show that ~ 70% of the variance in the datasets can be described using 7 dominant microstate templates. The mean duration and mean occurrence of the dominant microstates were significantly different in the two sleep states. Microstate syntax analysis demonstrated that the microstate sequences characterizing AS and QS had specific non-casual structures that differed in the two sleep states. Microstate analysis of the neonatal EEG in specific frequency bands showed a clear dependence of the explained variance on frequency. Overall, our findings demonstrate that (1) the spatio-temporal dynamics of the neonatal EEG can be described by non-casual sequences of a limited number of microstate templates; (2) the brain dynamics described by these microstate templates depends on frequency; (3) the features of the microstate sequences can well differentiate the physiological conditions characterizing AS and QS.

摘要

新生儿大部分时间都在睡觉。在睡眠过程中,他们的大脑经历着快速的功能组织变化。微状态分析通过将脑电图(EEG)的时空特征变化表示为短暂的头皮地形图序列(微状态),从而捕获大脑功能组织中的快速动态变化。在这项研究中,我们将新生儿的 EEG 模型化为有限数量的微状态序列,并研究了提取的微状态特征是否在 REM 和 NREM 睡眠中发生改变(通常在新生儿中称为活跃和安静睡眠状态-AS 和 QS),以及是否取决于 EEG 频带。我们使用改进的 k-均值聚类算法对 60 名足月健康婴儿的 19 通道 EEG 记录进行了分析。结果表明,数据集的约 70%可以用 7 个主要微状态模板来描述。两种睡眠状态下,主要微状态的平均持续时间和平均出现时间存在显著差异。微状态语法分析表明,AS 和 QS 特征的微状态序列具有特定的非偶然结构,在两种睡眠状态下有所不同。对特定频带的新生儿 EEG 进行微状态分析表明,解释方差与频率明显相关。总的来说,我们的研究结果表明:(1)新生儿 EEG 的时空动态可以用有限数量的微状态模板的非偶然序列来描述;(2)这些微状态模板所描述的大脑动态取决于频率;(3)微状态序列的特征可以很好地区分 AS 和 QS 特征的生理条件。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/71d6/8384814/46ffc608a740/10548_2021_861_Fig1_HTML.jpg

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