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Fine-Grained Parcellation of Brain Connectivity Improves Differentiation of States of Consciousness During Graded Propofol Sedation

机译:大脑连接性的细粒度分割可提高异丙酚分级镇静过程中意识状态的分化

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摘要

Conscious perception relies on interactions between spatially and functionally distinct modules of the brain at various spatiotemporal scales. These interactions are altered by anesthesia, an intervention that leads to fading consciousness. Relatively little is known about brain functional connectivity and its anesthetic modulation at a fine spatial scale. Here, we used functional imaging to examine propofol-induced changes in functional connectivity in brain networks defined at a fine-grained parcellation based on a combination of anatomical and functional features. Fifteen healthy volunteers underwent resting-state functional imaging in wakeful baseline, mild sedation, deep sedation, and recovery of consciousness. Compared with wakeful baseline, propofol produced widespread, dose-dependent functional connectivity changes that scaled with the extent to which consciousness was altered. The dominant changes in connectivity were associated with the frontal lobes. By examining node pairs that demonstrated a trend of functional connectivity change between wakefulness and deep sedation, quadratic discriminant analysis differentiated the states of consciousness in individual participants more accurately at a fine-grained parcellation (e.g., 2000 nodes) than at a coarse-grained parcellation (e.g., 116 anatomical nodes). Our study suggests that defining brain networks at a high granularity may provide a superior imaging-based distinction of the graded effect of anesthesia on consciousness.
机译:自觉感知依赖于各种时空尺度的大脑在空间和功能上不同的模块之间的相互作用。麻醉会改变这些相互作用,麻醉会导致意识消失。关于大脑功能连通性及其在精细空间尺度上的麻醉调节知之甚少。在这里,我们使用功能成像来检查异丙酚诱导的大脑网络中功能连接的变化,这些功能是基于解剖和功能特征的组合定义为细粒度的。 15名健康志愿者在基线醒来,轻度镇静,深度镇静和意识恢复后进行了静息状态功能成像。与唤醒基线相比,丙泊酚产生了广泛的,剂量依赖性的功能连通性变化,其随意识改变的程度而变化。连通性的主要变化与额叶相关。通过检查表明对觉醒和深度镇静之间的功能连通性变化趋势的节点对,二次判别分析在细粒度的分割(例如2000个节点)上比粗粒度的分割更准确地区分了单个参与者的意识状态。 (例如116个解剖结点)。我们的研究表明,以高粒度定义大脑网络可能会为基于麻醉效果的意识分级提供基于影像的出色区分。

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