Mechanisms of anesthetic-induced unconsciousness

麻醉引起的意识丧失的机制

• 批准号: 10387932
• 负责人: Matthew I Banks
• 金额: $ 11.9万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-02-15 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10387932
• 关键词: Algorithms; Anesthesia procedures; Anesthetics; Animal Model; Auditory; Awareness; Brain; Chronic; Code; Conscious; Data; Delirium; Development; Electrocorticogram; Electrophysiology (science); General Anesthesia; General anesthetic drugs; Goals; Human; Intractable Epilepsy; Knowledge; Measures; Medical; Mental disorders; Minimally Conscious States; Modeling; Monitor; Operative Surgical Procedures; Patients; Pattern; Play; Role; Schizophrenia; Sensory; Sleep; Structure; System; Testing; Time; Translating; Unconscious State; awake; clinical application; functional magnetic resonance imaging/electroencephalography; human subject; mental state; neural circuit; neural network; non-invasive monitor; novel; prognostic; remediation; research clinical testing; side effect

PROJECT SUMMARY The long-term objective of this proposal is to understand the mechanisms responsible for loss of consciousness (LOC) under general anesthesia. Previous invasive studies in animal models have identified candidate mechanisms, but translating those findings to human consciousness remains approximate. More precise determinations of states of consciousness are feasible in human subjects, but non-invasive measures of brain activity (fMRI, EEG, MEG) can only indirectly assess the underlying neural circuitry. This proposal will overcome these limitations by taking advantage of the unique opportunity to directly record from the human brain. Using electrocorticography in neurosurgical patients, we will investigate neural networks modulated by general anesthesia. Our overarching goal is to identify patterns of activity and connectivity in cortical networks that track changes in contents of consciousness (i.e. awareness) under anesthesia and during sleep. Our approach is to identify changes in the networks underlying auditory predictive coding that occur upon LOC. Predictive coding minimizes the differences between internally generated constructs and empirical data, subserved by ongoing interaction between sensory and higher-order cortical regions. This model is ideal for this project because it engages the crucial interplay between predictions of the world and sensory observations of the world, a fundamental function of consciousness. The scientific premise of this project is that at a systems level, disruption of predictive coding subserved by large-scale cortical networks represents a signature of anesthetic-induced unconsciousness. To accomplish our goals, we will pursue three specific aims. The first aim seeks to refine our understanding of the cortical networks involved in auditory predictive coding in awake behaving subjects. This aim will focus on identifying the connectivity of the networks subserving predictive coding over short and long time scales, as effects of LOC on these networks are believed to be distinct. The second aim examines changes in network structure upon anesthesia LOC. This will be achieved by recording brain activity from subjects during induction of general anesthesia. The generality of the findings will be tested using two different anesthetic agents. Aim 3 seeks to identify common electrophysiological signatures for LOC under anesthesia and during sleep. This will be achieved by measuring brain activity in the same subjects during natural sleep. The results will have broad clinical applicability to defining and interpreting prognostic signs in patients with altered mental status (e.g. chronic vegetative and minimally conscious states), mental illness (e.g. delirium and schizophrenia) and development of novel algorithms for use in monitoring depth of anesthesia.

项目总结 这项建议的长期目标是了解导致意识丧失的机制。 (LoC)在全身麻醉下。之前的动物模型侵入性研究已经确定了候选 机制，但将这些发现转化为人类意识仍然近似地。更精确 在人类受试者中确定意识状态是可行的，但对大脑的非侵入性测量 活动(fMRI、EEG、MEG)只能间接评估潜在的神经回路。这项提议将克服 这些限制通过利用独特的机会直接从人脑中记录下来。vbl.使用 神经外科患者的皮质脑电图，我们将研究普通神经网络的调制 麻醉。 我们的首要目标是确定大脑皮质网络中的活动和连通性模式，这些网络跟踪 麻醉和睡眠中的意识内容(即意识)。我们的方法是找出 发生在LOC上的听觉预测编码基础网络的变化。预测编码最大限度地减少了 内部生成的构造和经验数据之间的差异，由持续的交互作用提供支持 在感觉区域和高级皮质区域之间。此模型非常适合此项目，因为它与 对世界的预测和对世界的感官观察之间的关键相互作用，这是一项基本功能 意识的力量。该项目的科学前提是，在系统层面上，预测编码的中断 有大规模皮质网络的支持代表了麻醉剂诱导的无意识的特征。 为了实现我们的目标，我们将追求三个具体目标。第一个目标是试图完善我们对 大脑皮质网络参与清醒行为受试者的听觉预测编码。这一目标将集中在 识别在短和长时间尺度上辅助预测编码的网络的连通性，如 LOC对这些网络的影响被认为是不同的。第二个目标是检查网络的变化 麻醉后的结构。这将通过记录受试者在诱导过程中的大脑活动来实现 全身麻醉。将使用两种不同的麻醉剂来测试这些发现的一般性。目标3 寻求确定麻醉下和睡眠中LOC的共同电生理特征。这将是 通过测量相同受试者在自然睡眠期间的大脑活动来实现。结果将会有广泛的影响 定义和解释精神状态改变患者的预后体征的临床适用性(例如 慢性植物人和最低意识状态)、精神疾病(如精神错乱和精神分裂症)和 用于监测麻醉深度的新算法的开发。