识别严重脑损伤导致的内在脑动力学中断。

Sina Khanmohammadi, Terrance T Kummer, ShiNung Ching
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引用次数: 0

摘要

最近的研究表明,静息状态功能连通性的中断——一种衡量大脑区域之间静态统计关联的方法——可以作为脑损伤的客观标志。然而,研究脑损伤后内在脑动力学破坏的特征较少。在这里,我们使用脑损伤患者的脑电图(EEG)数据来研究这个问题,并进行对照分析,其中我们量化了损伤对内在事件反应穿越其各自状态空间的能力的影响。更具体地说,通过将获得的EEG信号的所有通道中的三个sigma事件反应折叠到一个低维空间来评估内在诱发脑活动的不稳定性。然后使用这些反应的方向导数来分析大脑活动达到低方差子空间的程度。我们的研究结果表明,从静息状态脑电图信号中提取的内在动力学可以区分严重昏迷病例的不同意识水平。更具体地说,在潜在动力学的状态-空间轨迹中,从一种状态转移到另一种状态的成本随着患者意识水平的恶化而降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Identifying Disruptions in Intrinsic Brain Dynamics due to Severe Brain Injury.

Recent studies suggest that disruptions in resting state functional connectivity - a measure of stationary statistical association between brain regions - can be used as an objective marker of brain injury. However, fewer characterizations have examined the disruption of intrinsic brain dynamics after brain injury. Here, we examine this issue using electroencephalographic (EEG) data from brain-injured patients, together with a control analysis wherein we quantify the effect of the injury on the ability of intrinsic event responses to traverse their respective state spaces. More specifically, the lability of intrinsically evoked brain activity was assessed by collapsing three sigma event responses in all channels of the obtained EEG signals into a low-dimensional space. The directional derivative of these responses was then used to assay the extent to which brain activity reaches low-variance subspaces. Our findings suggest that intrinsic dynamics extracted from resting state EEG signals can differentiate various levels of consciousness in severe cases of coma. More specifically the cost of moving from one state to another in the state-space trajectories of the underlying dynamics becomes lower as the level of consciousness of patients deteriorates.

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