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咪达唑仑诱导镇静期间意识状态转变时功能网络的变化。

Change in functional networks for transitions between states of consciousness during midazolam-induced sedation.

作者信息

Sanders Robert D, Tononi Giulio

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:958-961. doi: 10.1109/EMBC.2017.8036984.

DOI:10.1109/EMBC.2017.8036984
PMID:29060032
Abstract

How brain dynamics change across conscious states, including reliable signatures of the transitions between unconsciousness and consciousness, remains unclear. In this work, we addressed the changes in functional brain networks during self-titrated midazolam sedation using high-density electroencephalography (EEG) in ten subjects. We were particularly interested in the underlying network alterations, identified with graph theory, associated with transitions between states of consciousness. The weighted Phase Lag Index (wPLI) was used as the connectivity estimator between two signals. Based on wPLI, we calculated network properties such as characteristic path length, clustering coefficient, and small-worldness for measuring the integration and segregation of the brain network. We found significant changes in power and wPLI at different levels of consciousness. During unconsciousness, wPLI over the parietal region was higher in the delta band (1-4Hz). The frontal-parietal interaction in the delta band was also stronger during the transition from consciousness to unconsciousness. There was the significant difference of wPLI over the frontal region between consciousness and unconsciousness in the sigma band (12-15Hz). The topological properties across conscious states were significantly changed in the delta band and sigma band. Our results showed parietal brain dynamics is associated with consciousness. Our data also suggest that reversible changes in delta power and connectivity underlie changes in conscious state.

摘要

大脑动力学如何在不同意识状态下发生变化,包括无意识和意识之间转换的可靠特征,目前仍不清楚。在这项研究中,我们使用高密度脑电图(EEG)对10名受试者进行自我滴定咪达唑仑镇静时,研究了功能性脑网络的变化。我们特别关注通过图论识别出的与意识状态转换相关的潜在网络改变。加权相位滞后指数(wPLI)被用作两个信号之间的连通性估计器。基于wPLI,我们计算了网络属性,如特征路径长度、聚类系数和小世界特性,以测量脑网络的整合和分离。我们发现在不同意识水平下,功率和wPLI有显著变化。在无意识状态下,顶叶区域在δ波段(1-4Hz)的wPLI较高。在从意识向无意识转变过程中,δ波段的额顶叶相互作用也更强。在σ波段(12-15Hz),意识和无意识状态下额叶区域的wPLI存在显著差异。不同意识状态下的拓扑属性在δ波段和σ波段有显著变化。我们的结果表明顶叶脑动力学与意识相关。我们的数据还表明,δ功率和连通性的可逆变化是意识状态变化的基础。

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Brain-scale cortico-cortical functional connectivity in the delta-theta band is a robust signature of conscious states: an intracranial and scalp EEG study.
脑尺度的 delta-theta 频段皮质间功能连接是意识状态的稳健特征:一项颅内和头皮 EEG 研究。
Sci Rep. 2020 Aug 20;10(1):14037. doi: 10.1038/s41598-020-70447-7.
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EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions.脑电功能连接度量 wPLI 和 wSMI 可解释大脑功能交互的不同类型。
Sci Rep. 2019 Jun 20;9(1):8894. doi: 10.1038/s41598-019-45289-7.
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Connectivity differences between consciousness and unconsciousness in non-rapid eye movement sleep: a TMS-EEG study.非快速眼动睡眠中意识与无意识的连通性差异:一项 TMS-EEG 研究。
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