Brain Neurophysiological Biomarkers of Functional Recovery in Stroke

中风功能恢复的脑神经生理学生物标志物

• 批准号: 8635003
• 负责人: GEORGE F. WITTENBERG
• 金额: --
• 依托单位: BALTIMORE VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8635003
• 关键词: Activities of Daily Living; Affect; Algorithms; Bayesian Method; Behavior; Biological Markers; Brain; Cerebrum; Chronic; Chronic Phase; Classification; Clinical; Data; Development; Development Plans; Electroencephalography; Exhibits; Future; Goals; Individual; Investigation; Knowledge; Location; Mediating; Methods; Metric; Motor; Movement; Muscle; Neurobiology; Neurorehabilitation; Neurosciences; Outcome Measure; Outcome Study; Participant; Patients; Phase; Physiological; Play; Process; Real-Time Systems; Recovery; Recovery of Function; Rehabilitation device; Rehabilitation therapy; Reproducibility; Research; Resources; Rest; Robot; Robotics; Role; Sampling; Series; Signal Transduction; Staging; Stroke; Survivors; System; Testing; Therapeutic; Time; Upper Extremity; Upper arm; Veterans; Visit; Work; arm; base; brain computer interface; brain electrical activity; chronic stroke; clinical practice; critical period; disability; efficacy testing; experience; follow-up; functional improvement; hemiparetic stroke; improved; insight; kinematics; motor impairment; neuromechanism; neurophysiology; post stroke; public health relevance; rehabilitation strategy; relating to nervous system; robot assistance; stroke recovery

DESCRIPTION (provided by applicant): Background/Rationale: Stroke remains the leading cause of long-term disability in our Veterans and the vast majority of stroke survivors experience significant motor impairments in the upper extremity. Survivors of stroke regain the most function during the early phases of recovery, a process that is likely mediated by changes in underlying neurophysiology. These changes, however, are not well understood in relation to voluntary reaching movements, but are nonetheless critical to successful rehabilitation. Electroencephalography (EEG) is one of several methods to understand the mechanisms underlying recovery in stroke, but EEG-based investigations have mainly relied on global brain electrical activity (i.e. during resting state) t correlate with motor impairment and/or function. Our goal, therefore, is to better understand the neural mechanisms during planning and execution of volitional reach across critical periods of recovery. We intend to use EEG to identify changes in brain-derived biomarkers that reflect the timing and direction of the intent to reach, and determine how these change over the course of natural recovery, i.e., as stroke survivors progress from the subacute to chronic phases. Objectives: Our preliminary data indicate that it is feasible to collect quality EEG in survivors o stroke as they volitionally perform motor tasks. Moreover, we detected brain-derived biomarkers that reliably encoded for aspects of reach, i.e., the intended direction to move and timing of movement onset. Specifically the first study demonstrated that when using the proposed task a brain-derived biomarker could be extracted which encoded for the intended direction of reach. The second study revealed that using this same task, a chronic stroke patient exhibited well-characterized cortical dynamics associated with volitional movement. Further, using these biomarkers as input to a Bayesian classifier robustly predicted the timing of the intent to move on a trial- by-trial basis. Thus, the classification will only improve when many more brain-derived biomarkers are available to this classification system with regard to timing and direction. In lin with these preliminary studies, our objective is to characterize the neurophysiological signals that best predict the onset and direction of volitional reaching movements in survivors of stroke, and determine how these identified signals change as stroke survivors recover from subacute to chronic stages. Methods: A convenience sample of forty stroke patients will be studied in the subacute phase of recovery (2-6 weeks post-stroke) and followed to the chronic stage (> 6 months.) At each visit, participants will be asked to choose between, and reach to, one of two targets in an InMotion planar robot while EEG data are collected concurrently. The EEG time series corresponding to the period prior to movement onset will be extracted. These data will be processed in order to extract a multitude of functional EEG metrics (e.g., spectral power, coherence, and movement related cortical potentials.) These metrics will be used as inputs into a Bayesian classifier to determine which biomarkers reliably encode for volitional timing and direction of intended movement. Finally, the changes in these biomarkers as a function of recovery will be determined. Findings/Results: We predict that we will identify a subset of biomarkers from the multitude of EEG metrics that will consistently indicate the intended direction and timing of volitional movement. Further, we predict that these biomarkers will change as a function of recovery with regard to timing and location, and will therefore provide both mechanistic insights to recovery as well as data relevant to brain-computer interfaces. Status: This project is currently in the planning and development stage. Impact: This research will have a significant impact on steering future work aimed at maximizing functional recovery. Identifying the brain-derived biomarkers encoding for specific components of reach in stroke survivors will reveal the neurophysiology underlying natural recovery and guide future rehabilitation strategies.

描述（由申请人提供）： 背景/理由：中风仍然是退伍军人长期残疾的主要原因，绝大多数中风幸存者的上肢出现严重的运动障碍。中风幸存者在恢复的早期阶段恢复了大部分功能，这一过程可能是由潜在的神经生理学变化介导的。然而，这些变化与自愿伸展运动的关系还没有得到很好的理解，但对于成功康复至关重要。 脑电图（EEG）是了解中风恢复机制的几种方法之一，但基于脑电图的研究主要依赖于与运动损伤和/或功能相关的整体脑电活动（即静息状态期间）。因此，我们的目标是更好地理解在恢复的关键时期规划和执行意志力的过程中的神经机制。我们打算使用脑电图来识别脑源性生物标志物的变化，这些变化反映了达到意图的时间和方向，并确定这些变化在自然恢复过程中，即中风幸存者从亚急性阶段进展到慢性阶段时如何变化。目标：我们的初步数据表明，在中风幸存者自愿执行运动任务时收集高质量脑电图是可行的。此外，我们还检测到了脑源性生物标志物，这些生物标志物能够可靠地编码到达范围的各个方面，即预期的移动方向和运动开始的时间。具体来说，第一项研究表明，当使用所提出的任务时，可以提取脑源性生物标志物，该生物标志物编码了预期的到达方向。第二项研究表明，使用相同的任务，一名慢性中风患者表现出与意志运动相关的良好特征的皮质动力学。此外，使用这些生物标志物作为贝叶斯分类器的输入，可以在逐次试验的基础上稳健地预测移动意图的时间。因此，只有当更多的脑源性信息出现时，分类才会得到改善。 生物标志物可用于该分类系统的时间和方向。 与这些初步研究相一致，我们的目标是表征最能预测中风幸存者意志到达运动的发生和方向的神经生理学信号，并确定这些识别的信号随着中风幸存者从亚急性阶段恢复到慢性阶段如何变化。方法：将在亚急性恢复阶段（中风后 2-6 周）对 40 名中风患者的方便样本进行研究，并跟踪至慢性阶段（> 6 个月）。每次就诊时，参与者将被要求在 InMotion 平面机器人的两个目标之间进行选择并到达其中一个，同时收集脑电图数据。将提取与运动开始之前的时期相对应的脑电图时间序列。这些数据将被处理，以提取多种功能性脑电图指标（例如，光谱功率、相干性和运动相关的皮层电位）。这些指标将用作贝叶斯分类器的输入，以确定哪些生物标志物能够可靠地编码意图运动的意志时间和方向。最后，将确定这些生物标志物随恢复的变化。调查结果/结果：我们预测，我们将从众多脑电图指标中识别出生物标志物的子集，这些标志物将一致地指示意志运动的预期方向和时间。此外，我们预测这些生物标志物将随着恢复时间和位置的变化而变化，因此将提供恢复的机制见解以及与脑机接口相关的数据。状态：该项目目前处于规划和开发阶段。影响：这项研究将对指导未来旨在最大化功能恢复的工作产生重大影响。识别编码中风幸存者的特定部分的脑源性生物标志物将揭示自然恢复的神经生理学并指导未来的康复策略。