权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Mechanisms of Loss, Recovery and Disorders of Consciousness

意识丧失、恢复和障碍的机制

基本信息

批准号：
10607642
负责人：
Matthew I Banks
金额：
$ 62.26万
依托单位：
UNIVERSITY OF WISCONSIN-MADISON
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-02-15 至 2027-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10607642
关键词：
Acute Disease Algorithms Anesthesia procedures Arousal Attention Auditory Awareness Back Behavioral Biological Assay Biological Markers Brain Brain region Clinical Coma Computer Models Conscious Conscious Sedation Consciousness Disorders Data Delirium Development Diagnosis Dreams Drowsiness Drug Kinetics Electric Stimulation Electroencephalography Electrophysiology (science)Environment Epilepsy Exhibits Functional Magnetic Resonance Imaging General Anesthesia Human Impaired cognition Impairment Intractable Epilepsy Knowledge Magnetic Resonance Imaging Medical Memory Minimally Conscious States Modeling Monitor Operative Surgical Procedures Outcome Pathologic Patients Pattern Perception Perceptual disturbance Postoperative Period Probability Process Production Prognosis Recovery Reporting Resolution Rest Scalp structure Secondary to Sedation procedure Seizures Sensory Sleep Sleep Disorders Sleep Stages Speech Speech Perception Stimulus Structure Symptoms Testing Unconscious State Work awake biomarker identification clinically relevant executive function experimental study human subject improved innovation multimodality network models neural neural correlate neurosurgery novel potential biomarker remediation research clinical testing response sound specific biomarkers symptomatology

项目摘要

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.

项目概要该提案的长期目标是了解损失、恢复和恢复背后的皮质机制。意识障碍。我们之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。每个阶段都由不同的唤醒状态和意识，例如梦与无意识之间的波动。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。该提案需要利用独特的机会直接记录来自神经外科癫痫患者的人脑。我们将使用颅内脑电图（iEEG）来识别无意识和区别于三种不同的意识状态：清醒意识、睡意和梦境。该项目的科学前提是唤醒和临床相关变化的生物标志物意识具有共同的特征，超越了导致这些特征的特定条件。迄今为止我们的工作已经确定了假定的生物标志物，这些生物标志物有望区分唤醒和意识状态。这些生物标志物包括皮层对意外声音和言语反应的区域特异性变化，以及皮质连接模式。使用创新的计算方法应用于使用获得的数据通过电刺激和记录休息时持续的大脑活动，我们将跟踪皮质的快速转变网络配置。表征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。我们的多模式方法将高分辨率 iEEG 与计算建模、电刺激相结合人类重叠组中的束追踪、传统头皮记录脑电图和磁共振成像科目。我们将找到可靠的生物标志物，可以识别在发生过程中发生的不同意识状态。全身麻醉的诱导和苏醒（具体目标 1）以及睡眠的不同阶段（具体目标目标2）。然后，我们将利用这些生物标志物来了解谵妄的机制，谵妄可能发生在神经外科患者手术恢复期间和癫痫发作后（具体目标 3）。识别意识生物标志物与开发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，意识病理状态的管理和预后，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。

项目成果

期刊论文数量（21）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Postoperative Use of the Muscle Relaxants Baclofen and/or Cyclobenzaprine Associated With an Increased Risk of Delirium Following Lumbar Fusion.

术后使用肌肉松弛剂巴氯芬和/或环苯扎林会增加腰椎融合后谵妄的风险。

DOI：
10.1097/brs.0000000000004606
发表时间：
2023
期刊：
Spine
影响因子：
3
作者：
Perez,EliA;Ray,Emanuel;Gold,ColinJ;Park,BrianJ;Piscopo,Anthony;Carnahan,RyanM;Banks,Matthew;Sanders,RobertD;Olinger,CatherineR;Mueller,RashmiN;Woodroffe,RoyceW
通讯作者：
Woodroffe,RoyceW

Evaluation of putative signatures of consciousness using specific definitions of responsiveness, connectedness, and consciousness.

DOI：
10.1016/j.bja.2023.09.031
发表时间：
2023-10
期刊：
British journal of anaesthesia
影响因子：
9.8
作者：
Cameron P. Casey;Sean Tanabe;Zahra Farahbakhsh;Margaret Parker;Amber Bo;Marissa White;Tyler Ballweg;Andrew M. McIntosh;William Filbey;M. I. Banks;Y. Saalmann;Robert A. Pearce;Robert D. Sanders
通讯作者：
Cameron P. Casey;Sean Tanabe;Zahra Farahbakhsh;Margaret Parker;Amber Bo;Marissa White;Tyler Ballweg;Andrew M. McIntosh;William Filbey;M. I. Banks;Y. Saalmann;Robert A. Pearce;Robert D. Sanders

Characterising the effect of propofol on complexity and stability in the EEG power spectrum.