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一种不依赖于感觉处理和行为的基于理论的意识指标。

A theoretically based index of consciousness independent of sensory processing and behavior.

机构信息

Department of Biomedical and Clinical Sciences 'Luigi Sacco', University of Milan, 20157 Milan, Italy.

出版信息

Sci Transl Med. 2013 Aug 14;5(198):198ra105. doi: 10.1126/scitranslmed.3006294.

Abstract

One challenging aspect of the clinical assessment of brain-injured, unresponsive patients is the lack of an objective measure of consciousness that is independent of the subject's ability to interact with the external environment. Theoretical considerations suggest that consciousness depends on the brain's ability to support complex activity patterns that are, at once, distributed among interacting cortical areas (integrated) and differentiated in space and time (information-rich). We introduce and test a theory-driven index of the level of consciousness called the perturbational complexity index (PCI). PCI is calculated by (i) perturbing the cortex with transcranial magnetic stimulation (TMS) to engage distributed interactions in the brain (integration) and (ii) compressing the spatiotemporal pattern of these electrocortical responses to measure their algorithmic complexity (information). We test PCI on a large data set of TMS-evoked potentials recorded in healthy subjects during wakefulness, dreaming, nonrapid eye movement sleep, and different levels of sedation induced by anesthetic agents (midazolam, xenon, and propofol), as well as in patients who had emerged from coma (vegetative state, minimally conscious state, and locked-in syndrome). PCI reliably discriminated the level of consciousness in single individuals during wakefulness, sleep, and anesthesia, as well as in patients who had emerged from coma and recovered a minimal level of consciousness. PCI can potentially be used for objective determination of the level of consciousness at the bedside.

摘要

对脑损伤、无反应患者进行临床评估的一个挑战是缺乏一种独立于患者与外部环境交互能力的意识客观测量方法。理论考虑表明,意识取决于大脑支持复杂活动模式的能力,这些模式在同时分布在相互作用的皮质区域中(整合),并且在空间和时间上有所区分(信息丰富)。我们引入并测试了一种称为扰动复杂度指数(PCI)的基于理论的意识水平指标。PCI 通过以下方式计算:(i)用经颅磁刺激(TMS)刺激皮层,以在大脑中引发分布式相互作用(整合);(ii)压缩这些脑电反应的时空模式,以测量其算法复杂度(信息)。我们在一个由健康受试者在清醒、做梦、非快速眼动睡眠和不同镇静水平(咪达唑仑、氙气、丙泊酚)下记录的 TMS 诱发电位的大数据集中测试了 PCI,以及从昏迷中恢复的患者(植物状态、最小意识状态和闭锁综合征)。PCI 可靠地区分了个体在清醒、睡眠和麻醉期间以及从昏迷中恢复并恢复最低意识水平的意识水平。PCI 可能可用于床边客观确定意识水平。

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