Suppr超能文献

意识障碍中大脑网络大尺度连接变化的时程动力学:基于微观状态的研究。

The temporal dynamics of Large-Scale brain network changes in disorders of consciousness: A Microstate-Based study.

机构信息

Department of Neurosurgery, The First Hospital of Jilin University, Changchun, China.

Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

出版信息

CNS Neurosci Ther. 2023 Jan;29(1):296-305. doi: 10.1111/cns.14003. Epub 2022 Nov 1.

Abstract

BACKGROUND AND OBJECTIVES

The resting-state brain is composed of several discrete networks, which remain stable for 10-100 ms. These functional microstates are considered the building blocks of spontaneous consciousness. Electroencephalography (EEG) microstate analysis may provide insight into the altered brain dynamics underlying consciousness recovery in patients with disorders of consciousness (DOC). We aimed to analyze microstates in the resting-state EEG source space in patients with DOC, the relationship between state-specific features and consciousness levels, and the corresponding patterns of microstates and functional networks.

METHODS

We obtained resting-state EEG data from 84 patients with DOC (27 in a minimally conscious state [MCS] and 57 in a vegetative state [VS] or with unresponsive wakefulness syndrome). We conducted a microstate analysis of the resting-state (EEG) source space and developed a state-transition analysis protocol for patients with DOC.

RESULTS

We identified seven microstates with distinct spatial distributions of cortical activation. Multivariate pattern analyses revealed that different functional connectivity patterns were associated with source-level microstates. There were significant differences in the microstate properties, including spatial activation patterns, temporal dynamics, state shifts, and connectivity construction, between the MCS and VS groups.

DISCUSSION

Our findings suggest that consciousness depends on complex dynamics within the brain and may originate from the anterior cortex.

摘要

背景与目的

静息态大脑由几个离散的网络组成,这些网络在 10-100ms 内保持稳定。这些功能微状态被认为是自发性意识的构建模块。脑电(EEG)微状态分析可能有助于深入了解意识障碍(DOC)患者意识恢复背后的大脑动力学变化。我们旨在分析 DOC 患者静息态 EEG 源空间中的微状态,研究特定状态特征与意识水平之间的关系,以及相应的微状态和功能网络模式。

方法

我们从 84 名 DOC 患者(27 名处于最小意识状态(MCS),57 名处于植物状态(VS)或无反应觉醒综合征)中获得了静息态 EEG 数据。我们对静息态 EEG 源空间进行了微状态分析,并为 DOC 患者制定了状态转换分析方案。

结果

我们确定了七个具有不同皮质激活空间分布的微状态。多元模式分析显示,不同的功能连接模式与源水平微状态相关。MCS 和 VS 组之间的微状态特性存在显著差异,包括空间激活模式、时间动态、状态转换和连接构建。

讨论

我们的研究结果表明,意识依赖于大脑内部的复杂动力学,可能起源于前皮质。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b84/9804064/a96c031004f3/CNS-29-296-g004.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验