Kafashan MohammadMehdi, Ching ShiNung, Palanca Ben J A
Department of Electrical and Systems Engineering, Washington University in St. Louis St. Louis, MO, USA.
Department of Electrical and Systems Engineering, Washington University in St. LouisSt. Louis, MO, USA; Division of Biology and Biomedical Science, Washington University in St. LouisSt. Louis, MO, USA.
Front Neural Circuits. 2016 Dec 27;10:107. doi: 10.3389/fncir.2016.00107. eCollection 2016.
The spatiotemporal patterns of correlated neural activity during the transition from wakefulness to general anesthesia have not been fully characterized. Correlation analysis of blood-oxygen-level dependent (BOLD) functional magnetic resonance imaging (fMRI) allows segmentation of the brain into resting-state networks (RSNs), with functional connectivity referring to the covarying activity that suggests shared functional specialization. We quantified the persistence of these correlations following the induction of general anesthesia in healthy volunteers and assessed for a dynamic nature over time. We analyzed human fMRI data acquired at 0 and 1.2% vol sevoflurane. The covariance in the correlated activity among different brain regions was calculated over time using bounded Kalman filtering. These time series were then clustered into eight orthogonal motifs using a K-means algorithm, where the structure of correlated activity throughout the brain at any time is the weighted sum of all motifs. Across time scales and under anesthesia, the reorganization of interactions between RSNs is related to the strength of dynamic connections between member pairs. The covariance of correlated activity between RSNs persists compared to that linking individual member pairs of different RSNs. Accounting for the spatiotemporal structure of correlated BOLD signals, anesthetic-induced loss of consciousness is mainly associated with the disruption of motifs with intermediate strength within and between members of different RSNs. In contrast, motifs with higher strength of connections, predominantly with regions-pairs from within-RSN interactions, are conserved among states of wakefulness and sevoflurane general anesthesia.
从清醒状态过渡到全身麻醉期间相关神经活动的时空模式尚未得到充分表征。基于血氧水平依赖(BOLD)的功能磁共振成像(fMRI)的相关性分析可将大脑分割为静息态网络(RSN),功能连接性指的是共同变化的活动,这表明存在共享的功能特化。我们量化了健康志愿者全身麻醉诱导后这些相关性的持续性,并评估了其随时间的动态性质。我们分析了在0和1.2%体积分数七氟醚条件下采集的人类fMRI数据。使用有界卡尔曼滤波计算不同脑区之间相关活动的协方差随时间的变化。然后使用K均值算法将这些时间序列聚类为八个正交模式,其中大脑在任何时刻相关活动的结构是所有模式的加权和。在不同时间尺度和麻醉状态下,RSN之间相互作用的重组与成员对之间动态连接的强度有关。与连接不同RSN的单个成员对的协方差相比,RSN之间相关活动的协方差持续存在。考虑到相关BOLD信号的时空结构,麻醉诱导的意识丧失主要与不同RSN内和之间中等强度模式的破坏有关。相比之下,连接强度较高的模式,主要是来自RSN内相互作用的区域对,在清醒状态和七氟醚全身麻醉状态下是保守的。