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意识障碍患者脑电源空间网络整合能力下降。

Decreased integration of EEG source-space networks in disorders of consciousness.

机构信息

Univ Rennes, LTSI, F-35000 Rennes, France; Azm Center for Research in Biotechnology and its Applications, EDST, Lebanese University, Lebanon.

GIGA Consciousness, University of Liège, Liège, Belgium; Coma Science Group, University Hospital of Liège, Liège, Belgium.

出版信息

Neuroimage Clin. 2019;23:101841. doi: 10.1016/j.nicl.2019.101841. Epub 2019 Apr 29.

Abstract

Increasing evidence links disorders of consciousness (DOC) with disruptions in functional connectivity between distant brain areas. However, to which extent the balance of brain network segregation and integration is modified in DOC patients remains unclear. Using high-density electroencephalography (EEG), the objective of our study was to characterize the local and global topological changes of DOC patients' functional brain networks. Resting state high-density-EEG data were collected and analyzed from 82 participants: 61 DOC patients recovering from coma with various levels of consciousness (EMCS (n = 6), MCS+ (n = 29), MCS- (n = 17) and UWS (n = 9)), and 21 healthy subjects (i.e., controls). Functional brain networks in five different EEG frequency bands and the broadband signal were estimated using an EEG connectivity approach at the source level. Graph theory-based analyses were used to evaluate their relationship with decreasing levels of consciousness as well as group differences between healthy volunteers and DOC patient groups. Results showed that networks in DOC patients are characterized by impaired global information processing (network integration) and increased local information processing (network segregation) as compared to controls. The large-scale functional brain networks had integration decreasing with lower level of consciousness.

摘要

越来越多的证据表明意识障碍(DOC)与大脑远隔区域之间功能连接的中断有关。然而,DOC 患者大脑网络的分离和整合平衡在多大程度上发生了改变尚不清楚。本研究使用高密度脑电图(EEG),旨在描述 DOC 患者功能大脑网络的局部和全局拓扑变化。从 82 名参与者中收集和分析了静息状态高密度 EEG 数据:61 名从昏迷中恢复过来的意识障碍患者(有不同程度的意识,即昏迷后意识状态评分 6 分(n=6)、最小意识状态(MCS+)(n=29)、MCS-(n=17)和植物状态(UWS)(n=9))和 21 名健康对照者(即健康志愿者)。使用源水平 EEG 连接方法估计了五个不同 EEG 频带和宽带信号的功能大脑网络。基于图论的分析用于评估它们与意识水平下降的关系以及健康志愿者和 DOC 患者组之间的组间差异。结果表明,与对照组相比,DOC 患者的网络表现为全局信息处理受损(网络整合)和局部信息处理增加(网络分离)。大尺度功能大脑网络的整合随着意识水平的降低而降低。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ebc5/6503216/ecaac8816674/gr1.jpg

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