Stroke Plasticity

行程可塑性

• 批准号: 8593893
• 负责人: Vivek Prabhakaran
• 金额: $ 19.09万
• 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: 2014-01-15 至 2017-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8593893
• 关键词: Activities of Daily Living; Acute; Adult; Adverse effects; Aging; American; Applications Grants; Area; Behavior; Behavioral; Biofeedback; Brain; Brain Injuries; Brain Part; Brain region; Caregivers; Cause of Death; Chronic; Clinical; Contralateral; Decision Making; Development; Disease; Educational workshop; Elderly; Evaluation; Functional Magnetic Resonance Imaging; Future; Guidelines; Health; Healthcare; High Prevalence; Intervention; Language; Lead; Link; Long-Term Care; Longevity; Machine Learning; Measures; Methods; Motor; Neuronal Plasticity; Neurosciences Research; Occupational; Outcome; Patients; Pattern; Performance; Phase; Process; Recommendation; Recovery; Recovery of Function; Recruitment Activity; Recurrence; Rehabilitation therapy; Research; Research Proposals; Rest; Robot; Scanning; Severities; Signal Transduction; Speech Therapy; Staging; Stroke; Techniques; Time; Transcranial magnetic stimulation; Translations; United States; United States National Institutes of Health; Vascular blood supply; aging population; base; behavior test; brain computer interface; clinical application; constraint induced therapy; cost; design; disability; economic cost; functional disability; improved; indexing; neuroimaging; novel; post stroke; prognostic; rehabilitation strategy; stroke recovery; stroke rehabilitation; therapy development; tool; treatment planning

DESCRIPTION (provided by applicant): Stroke occurs when blood supply to some part of the brain is compromised and can lead to focal motor, language, and general functional deficits important for activities of daily life. Recovery after deficits in stroke patients is linked to bran plasticity changes occurring over time. There is evidence that these plasticity changes can be adaptive as well as maladaptive towards functional recovery and rehabilitation aimed at facilitating adaptive networks and suppressing maladaptive networks may hasten stroke recovery1-7. One way to characterize plasticity changes over time is by utilizing fMRI methods in adults who have suffered an insult (e.g., stroke) resulting in damage to an area typically associated with a specific language or motor function. Studies have shown that these patients show recovery through brain reorganization changes over time where a network of areas are recruited while performing the language or motor function1-7. There are a number of novel stroke rehabilitation treatments aimed at improving recovery. Yet no set guidelines exist on how to utilize these treatments. There is an important need to develop a set of prognostic predictors to make decisions about which patients are appropriate for which treatment, identify a time window that best predicts stroke recovery and therefore ideal for intervention, as well as characterize adaptive and maladaptive brain plasticity changes in order to facilitate faster and more effective rehabilitation. This proposal has three aims: 1) Identify prognostic predictors of stroke recovery, 2) Identify a time window which best predicts stroke recovery, and 3) Identify adaptive and maladaptive brain plasticity changes involved in stroke recovery. Stroke patients will undergo through neuroimaging and behavioral testing at the acute, subacute and chronic stages. Neuroimaging measures (e.g., fMRI activation) along with clinical measures will be utilized to predict behavior. It is hypothesized that neuroimaging along with clinical measures will predict motor, language, and general functional stroke recovery more accurately than either measure. It is also hypothesized a subacute time window would best predict stroke recovery, given that the most robust plasticity changes occur at this time window. It is hypothesized that that brain plasticity changes assessed by brain measures over time will predict behavioral performance changes over time, characterizing adaptive and maladaptive plasticity networks essential for motor, language, and general functional stroke recovery. Overall this would lead to better prognostic prediction of recovery in stroke patients, identify a critical time window for intervention, identify adaptive and maladaptive networks involved in reorganization. Subsequently this would allow us to provide individualized treatments based on the prognostics, allow us to intervene at a particular time window for optimal effect, and expand the potential for a range of rehabilitation strategies aimed at facilitating adaptive and suppressing maladaptive networks hastening and maximizing functional recovery.

描述（由申请人提供）：当大脑某些部分的血液供应受到损害并可能导致焦点运动，语言和一般功能缺陷对日常生活活动很重要时，就会发生中风。中风患者缺陷后的恢复与随着时间的流逝发生的麸皮可塑性变化有关。有证据表明，这些可塑性变化可以是适应性的，并且适应不良的功能恢复和康复，旨在促进自适应网络和抑制不良适应网络，可能会加速中风恢复1-7。表征可塑性随时间变化的一种方法是利用受侮辱（例如，中风）的成年人中的fMRI方法，从而损害了与特定语言或运动功能相关的区域。研究表明，这些患者通过招募语言或运动功能时招募了区域网络的脑部重组会发生恢复。1-7。有许多新型的中风康复治疗旨在改善恢复。然而，如何利用这些治疗方法尚无固定准则。重要的是要开发一组预后预测因子，以决定哪些患者适合哪种治疗，确定一个可以预测中风恢复并因此理想干预的时间窗口，并表征适应性和适应不良的大脑可塑性的变化，以促进更快，更有效的康复。该提议具有三个目的：1）确定的预后预测指标 中风恢复，2）确定一个最能预测中风恢复的时间窗口，3）确定中风恢复中涉及的适应性和适应不良的脑可塑性变化。中风患者将通过在急性，亚急性和慢性阶段进行神经影像和行为测试进行。神经影像措施（例如，fMRI激活）以及临床措施将用于预测行为。假设神经影像与临床措施一起将比任何一种方法都更准确地预测运动，语言和一般功能性中风恢复。还假设一个亚急性时间窗口可以最好地预测中风恢复，因为在此时间窗口中发生了最强大的可塑性变化。假设，随着时间的推移，通过大脑测量评估的大脑可塑性变化会预测行为性能随时间的变化，表征适应性和适应不良的可塑性网络，对运动，语言和一般功能性中风恢复至关重要。总体而言，这将导致中风患者恢复的预后预测，并确定关键时间窗口 干预，确定与重组有关的适应性和适应不良网络。随后，这将使我们能够根据预后来提供个性化的治疗方法，使我们能够在特定时间窗口中进行干预以获得最佳效果，并扩大了旨在促进适应性和抑制不良适应网络的一系列康复策略的潜力，从而促进和最大化功能恢复。