Department of Physics, Pohang University of Science and Technology, Pohang, Korea.
Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Hum Brain Mapp. 2017 Oct;38(10):4980-4995. doi: 10.1002/hbm.23708. Epub 2017 Jul 3.
Recent evidence suggests that the conscious brain is characterized by a diverse repertoire of functional connectivity patterns while the anesthetized brain shows stereotyped activity. However, classical time-averaged methods of connectivity dismiss dynamic and temporal characteristics of functional configurations. Here we demonstrate a new approach which characterizes time-varying patterns of functional connectivity at the subsecond time scale.
We introduce phase-lag entropy (PLE), a measure of the diversity of temporal patterns in the phase relationships between two signals. The proposed measure was applied to multichannel electroencephalogram (EEG), which were recorded from two distinct experimental settings: (1) propofol was administrated at a constant infusion rate for 60 min (n = 96); (2) administration of propofol by a target effect-site concentration-controlled infusion with simultaneous assessment of the level of consciousness (n = 10).
From the first dataset, two substantial changes of the phase relationship during anesthesia was found: (1) the dynamics of the phase relationship between frontal channels became progressively less diverse and more stereotyped during unconsciousness, quantified as a reduction in PLE; and (2) the reduction in PLE was consistent across subjects. Furthermore, PLE provided better performance in the classification of states of consciousness than did phase-lag index, a classical time-averaged connectivity method. From the second dataset, PLE showed the highest agreement with the level of consciousness, compared to existing anesthetic depth indicators.
This study suggests that a scarcity of functional configurations is closely associated with anesthetically induced unconsciousness, and shows promise as a basis for a new consciousness monitoring system during general anesthesia. Hum Brain Mapp 38:4980-4995, 2017. © 2017 Wiley Periodicals, Inc.
最近的证据表明,意识大脑的特征是功能连接模式的多样化,而麻醉大脑则表现出刻板的活动。然而,经典的时间平均连接方法忽略了功能配置的动态和时间特征。在这里,我们展示了一种新的方法,可以在亚秒级的时间尺度上描述功能连接的时变模式。
我们引入了相位滞后熵(PLE),这是衡量两个信号之间相位关系的时间模式多样性的一种度量。所提出的度量方法应用于多通道脑电图(EEG),这些 EEG 是在两个不同的实验设置中记录的:(1)以恒定输注速率输注丙泊酚 60 分钟(n=96);(2)通过目标效应部位浓度控制输注给予丙泊酚,同时评估意识水平(n=10)。
从第一个数据集发现,麻醉期间相位关系发生了两个实质性变化:(1)在无意识状态下,前额通道之间的相位关系的动力学变得越来越缺乏多样性和刻板,PLE 降低可以量化这种变化;(2)PLE 的降低在所有受试者中都是一致的。此外,与经典的时间平均连接方法——相位滞后指数相比,PLE 在意识状态分类中的表现更好。从第二个数据集,与现有的麻醉深度指标相比,PLE 与意识水平的一致性最高。
这项研究表明,功能配置的缺乏与麻醉诱导的无意识密切相关,并有望成为全身麻醉期间新的意识监测系统的基础。人类大脑映射 38:4980-4995,2017。©2017 威利期刊公司