Network Efficiency and Posterior Alpha Patterns Are Markers of Recovery from General Anesthesia: A High-Density Electroencephalography Study in Healthy Volunteers.
Network Efficiency and Posterior Alpha Patterns Are Markers of Recovery from General Anesthesia: A High-Density Electroencephalography Study in Healthy Volunteers.
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DOI：
10.3389/fnhum.2017.00328
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发表时间：
2017
影响因子：
2.9
通讯作者：
Mashour GA
中科院分区：
文献类型：
--
作者：
Blain-Moraes S;Tarnal V;Vanini G;Bel-Behar T;Janke E;Picton P;Golmirzaie G;Palanca BJA;Avidan MS;Kelz MB;Mashour GA
最近的研究调查了局部振荡、远程连接和全局网络模式，以确定与麻醉诱导的无意识相关的神经变化。这些研究通常采用麻醉方案，要么刚刚越过无意识的门槛，要么在短时间内诱发深度无意识——这两种方法都不能模拟大手术的全身麻醉。为了在临床相关的背景下研究无意识和恢复的神经模式，我们使用了一种现实的麻醉方案来诱导和维持8名健康参与者的无意识3小时。在整个过程中以及在苏醒后3小时获得高密度脑电图（EEG）。从基线以及出现后30、60、90、120、150和180分钟的数据中提取7个5分钟闭眼静息状态。此外，在诱导、无意识和意识恢复之前提取5分钟时间，共10个分析时间。利用源定位谱分析、相位滞后指数和图论技术对各历元的脑电数据进行分析。后阿尔法功率在无意识状态下显著降低，并在3小时的恢复期逐渐接近基线水平。相位滞后指数不能区分意识状态和恢复阶段。在无意识状态下，网络效率显著降低，网络聚类系数显著升高；在3小时的恢复期，这些图形理论测量值恢复到基线。脑后功率可能是全麻后脑功能网络正常恢复的潜在生物标志物。
Recent studies have investigated local oscillations, long-range connectivity, and global network patterns to identify neural changes associated with anesthetic-induced unconsciousness. These studies typically employ anesthetic protocols that either just cross the threshold of unconsciousness, or induce deep unconsciousness for a brief period of time—neither of which models general anesthesia for major surgery. To study neural patterns of unconsciousness and recovery in a clinically-relevant context, we used a realistic anesthetic regimen to induce and maintain unconsciousness in eight healthy participants for 3 h. High-density electroencephalogram (EEG) was acquired throughout and for another 3 h after emergence. Seven epochs of 5-min eyes-closed resting states were extracted from the data at baseline as well as 30, 60, 90, 120, 150, and 180-min post-emergence. Additionally, 5-min epochs were extracted during induction, unconsciousness, and immediately prior to recovery of consciousness, for a total of 10 analysis epochs. The EEG data in each epoch were analyzed using source-localized spectral analysis, phase-lag index, and graph theoretical techniques. Posterior alpha power was significantly depressed during unconsciousness, and gradually approached baseline levels over the 3 h recovery period. Phase-lag index did not distinguish between states of consciousness or stages of recovery. Network efficiency was significantly depressed and network clustering coefficient was significantly increased during unconsciousness; these graph theoretical measures returned to baseline during the 3 h recovery period. Posterior alpha power may be a potential biomarker for normal recovery of functional brain networks after general anesthesia.