Gong Anjuan, Wang Qijun, Guo Qian, Yang Ying, Chen Xuewei, Hu Xiaohua, Zhang Ying
Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China.
Hangzhou Normal University School of Nursing, Hangzhou, Zhejiang, China.
Front Neurol. 2024 Feb 15;15:1283140. doi: 10.3389/fneur.2024.1283140. eCollection 2024.
Most brain function assessments for disorders of consciousness (DOC) utilized quantified characteristics, measured only once, ignoring the variation of patients' brain states. The study aims to investigate the brain activities of patients with DOC from a new perspective: variability of a large timescale functional network.
Forty-nine patients were enrolled in this study and performed a 1-week behavioral assessment. Subsequently, each patient received electroencephalography (EEG) recordings five times daily at 2-h intervals. Functional connectivity and networks were measured by weighted phase lag index and complex network parameters (characteristic path length, cluster coefficient, and betweenness centrality). The relative coefficient of variation (CV) of network parameters was measured to evaluate functional network variability.
Functional networks of patients with vegetative state/unresponsive wakefulness syndrome (VS/UWS) showed significantly higher segregation (characteristic path length) and lower centrality (betweenness centrality) than emerging from the minimal conscious state (EMCS) and minimal conscious state (MCS), as well as lower integration (cluster coefficient) than MCS. The functional networks of VS/UWS patients consistently presented the highest variability in segregation and integration (i.e., highest CV values of characteristic path length and cluster coefficient) on a larger time scale than MCS and EMCS. Moreover, the CV values of characteristic path length and cluster coefficient showed a significant inverse correlation with the Coma Recovery Scale-Revised scores (CRS-R). The CV values of network betweenness centrality, particularly of the cento-parietal region, showed a positive correlation with the CRS-R.
The functional networks of VS/UWS patients present the most invariant segregation and integration but divergent centrality on the large time scale networks than MCS and EMCS.
The variations observed within large timescale functional networks significantly correlate with the degree of consciousness impairment. This finding augments our understanding of the neurophysiological mechanisms underpinning disorders of consciousness.
大多数用于意识障碍（DOC）的脑功能评估采用仅测量一次的量化特征，而忽略了患者脑状态的变化。本研究旨在从一个新的角度研究DOC患者的脑活动：大时间尺度功能网络的变异性。
49名患者参与本研究并进行了为期1周的行为评估。随后，每位患者每天接受5次脑电图（EEG）记录，间隔2小时。通过加权相位滞后指数和复杂网络参数（特征路径长度、聚类系数和介数中心性）测量功能连接性和网络。测量网络参数的相对变异系数（CV）以评估功能网络变异性。
与最低意识状态（EMCS）和最低意识状态（MCS）相比，植物状态/无反应觉醒综合征（VS/UWS）患者的功能网络显示出明显更高的隔离度（特征路径长度）和更低的中心性（介数中心性），并且与MCS相比整合度（聚类系数）更低。在比MCS和EMCS更大的时间尺度上，VS/UWS患者的功能网络在隔离和整合方面始终表现出最高的变异性（即特征路径长度和聚类系数的最高CV值）。此外，特征路径长度和聚类系数的CV值与昏迷恢复量表修订版评分（CRS-R）呈显著负相关。网络介数中心性的CV值，特别是中央顶叶区域的CV值，与CRS-R呈正相关。
与MCS和EMCS相比，VS/UWS患者的功能网络在大时间尺度网络上呈现出最不变的隔离和整合，但中心性不同。
在大时间尺度功能网络中观察到的变化与意识障碍程度显著相关。这一发现加深了我们对意识障碍背后神经生理机制的理解。
