Mechanisms of Loss, Recovery and Disorders of Consciousness

项目摘要 这项建议的长期目标是了解大脑皮层机制的损失，恢复， 意识障碍我们先前已经描述了与不同阶段相关的神经活动 全身麻醉和睡眠。这些阶段中的每一个都由不同的唤醒状态组成， 意识，如做梦和无意识之间的波动。寻找神经基础 这些过程对于理解意识的神经基础是必要的。这项提议需要 这是一个独特的机会，直接记录从人类大脑神经外科癫痫患者的优势。 我们将使用颅内脑电图（iEEG）来识别无意识的特征， 将它与三种不同的意识状态区分开来：清醒的意识，困倦和做梦。 这个项目的科学前提是，临床相关的生物标志物的变化，唤醒和 意识具有共同的特征，超越了导致它们的特定条件。我们迄今为止的工作 已经确定了假定的生物标志物，显示出区分唤醒和意识状态的希望。这些 生物标志物包括皮质对意外声音和言语的反应的区域特异性变化，以及皮质对意外声音和言语的反应的区域特异性变化。 皮层连接的模式利用创新的计算方法， 电刺激和记录休息时正在进行的大脑活动，我们将跟踪皮层的快速转换， 网络配置。描述这些快速转变将使我们能够识别临床相关的 觉醒和意识的变化。 我们的多模态方法将高分辨率iEEG与计算建模、电刺激 在重叠人群中进行的束追踪、常规头皮记录EEG和磁共振成像 科目我们将找到可靠的生物标志物，可以识别不同的意识状态， 全身麻醉的诱导和苏醒（具体目标1）和睡眠的不同阶段（具体 目标2）。然后，我们将利用这些生物标志物来了解谵妄的机制，这可能发生在 手术恢复期和癫痫发作后的神经外科患者（特定目标3）。 识别意识的生物标志物对于开发用于识别意识的新算法具有广泛的临床相关性。 监测麻醉深度。从该项目中获得的知识将有助于改进诊断， 对包括中枢性睡眠障碍，谵妄， 植物人或最低意识状态以及昏迷

PROJECT SUMMARY The long-term objective of this proposal is to understand cortical mechanisms underlying loss, recovery, and disorders of consciousness. We have previously characterized neural activity associated with different stages of general anesthesia and sleep. Each of these stages is composed of distinct states of arousal and awareness, such as fluctuations between dreaming and unconsciousness. Finding neural underpinnings of these processes is necessary for understanding the neural basis of consciousness. This proposal takes advantage of the unique opportunity to directly record from the human brain in neurosurgical epilepsy patients. We will use intracranial electroencephalography (iEEG) to identify signatures of unconsciousness and distinguish it from three different states of consciousness: waking consciousness, drowsiness, and dreaming. The scientific premise of this project is that the biomarkers of clinically relevant changes in arousal and awareness share common features, generalizing beyond specific conditions that cause them. Our work to date has identified putative biomarkers that show promise for distinguishing states of arousal and awareness. These biomarkers include region-specific changes in cortical responses to unexpected sounds and speech, and in patterns of cortical connectivity. Using innovative computational approaches applied to data obtained using electrical stimulation and recording of ongoing brain activity at rest, we will track rapid transitions in cortical network configurations. Characterizing these rapid transitions will enable us to identify clinically relevant changes in arousal and awareness. Our multimodal approach combines high resolution iEEG with computational modeling, electrical stimulation tract tracing, conventional scalp-recorded EEG, and magnetic resonance imaging in overlapping sets of human subjects. We will find reliable biomarkers that can identify distinct states of consciousness that occur during induction of and emergence from general anesthesia (Specific Aim 1) and different stages of sleep (Specific Aim 2). We will then leverage these biomarkers to understand mechanisms of delirium, which can occur in neurosurgical patients during recovery from surgery and following seizures (Specific Aim 3). Identifying biomarkers of consciousness has broad clinical relevance to development of novel algorithms for monitoring depth of anesthesia. Knowledge gained from this project will contribute to improved diagnosis, management and prognosis of pathologic states of consciousness including central sleep disorders, delirium, vegetative or minimally conscious states, and coma.