Targeting Neuroplasticity with Brain Computer Interfaces to Maximize Motor Recovery for Veterans with Stroke

中风每年影响15,000多名退伍军人，是后天成人残疾的主要原因 在美国。改善中风退伍军人的功能残疾是退伍军人退伍军人协会的高度优先事项 医疗保健系统。中风后上肢无力是功能障碍的主要来源 三分之二的中风幸存者在6个月时无法将患病的手臂纳入日常生活活动 中风后。与近年来急性卒中护理的变革性进展形成对比的是，治疗急性卒中的新疗法 中风后的康复仍然有限。卒中后手臂运动的临床研究现状 康复仍然是职业和物理治疗。这些标准方法目前不是 了解中风后神经解剖损伤或神经生理学。 脑机接口(BCI)是一种很有前途的中风康复新技术。超越 通过允许人们控制计算机光标来恢复通信来取代失去的运动功能 或者机器人假肢来恢复运动，BCI还具有增强神经康复的潜力。这个 康复BCI的基本原理是将预期的手臂运动的神经活动(即 通过EEG)到实际手臂运动的感觉运动反馈(即通过手臂矫形器)重建Hebbian 最大限度地激活神经回路和恢复神经功能所需的环境。小规模的研究 改善中风患者康复的BCI已经显示出一些希望，但其机制是通过 哪些BCI能够实现复苏一直没有得到充分的研究。因此，重要的问题仍然摆在我们面前。 BCI对中风康复有意义的临床翻译是可能发生的。哪些患者会 最佳受益于BCI神经康复？卒中后脑机接口训练的最佳时间段是什么？ 在这个拟议的职业发展申请中，我将利用一个独特的和正在进行的临床研究 普罗维登斯退伍军人医疗中心和马萨诸塞州综合医院的基础设施，该医院已经招募了 在两年半的时间里，有120多名急性中风患者出现手臂无力，并对这些患者进行了 接受Fugl-Meyer和Upper的手臂运动结果测量的第一年的康复过程 肢体运动学、神经成像和神经生理学。我将通过添加EEG来直接扩展这项研究- BCI手臂矫形器在四个研究时间点进行治疗，第一次治疗发生在中风后的几天内。 我的第一个目标是确定单一的-1诱导的皮质功能连接的纵向变化。 EEG-BCI手臂矫形器训练课程。我将研究特定的神经回路，它们通过 EEG-BCI训练和中风后对训练最敏感的电路的时间窗口。我的第二个 目的是评估基线手臂运动严重程度和中风神经解剖学如何调节EEG的效果。 BCI手臂矫形器皮质功能连通性训练。我将调查ARM Fugl-Meyer的影响 结构损伤对特定解剖结构的脑电-脑电诱发的环路改变。此外，这一点 该项目将允许我将我的研究和临床职业生涯整合到退伍军人管理局系统中，并将为我提供 脑网络量化、神经工程和纵向分析的基本科学工具 运动表现和康复结果的评估，由基于退伍军人管理局的卓越指导团队提供支持。 该项目具有(1)创新性，因为它直接扩展了 普罗维登斯VAMC和MGH为神经技术和神经恢复提供了一个特殊的环境， 据我所知，在世界其他地方是找不到的(2)有影响力的是因为对 EEG-BCI治疗手臂运动神经康复的神经机制将取得进展 BCI神经技术的临床应用；(3)意义重大，因为它是VA整合的第一步 这将最终为我提供一个机会，带领一个退伍军人事务部团队在临床上翻译BCI 使中风后退伍军人能够最大限度地恢复功能和提高生活质量的技术。

Stroke affects more than 15,000 Veterans per year and is the leading cause of acquired adult disability in the United States. Improving functional disability for Veterans with stroke is a high priority for the VA healthcare system. Upper extremity weakness after stroke is a major source of functional disability with over two-thirds of stroke survivors unable to incorporate their affected arm into activities of daily life at six months post-stroke. In contrast to transformative advances in acute stroke care in recent years, novel therapies for rehabilitation after stroke remain limited. The current clinical state-of-the-art for post-stroke arm motor rehabilitation remains occupational and physical therapies. These standard approaches are not currently informed by post-stroke neuroanatomic injury or neurophysiology. Brain computer interfaces (BCIs) are a promising novel technology for stroke rehabilitation. Beyond substituting for lost motor function by allowing people to control computer cursors to regain communication or robot prosthetics to restore movement, BCIs also have the potential to enhance neurorehabilitation. The underlying principle of a rehabilitative BCI is that linking the neural activity of intended arm movement (i.e. via EEG) to the sensorimotor feedback of actual arm movement (i.e. via arm orthosis) recreates the Hebbian environment needed to maximally engage neural circuits and restore neurologic function. Small studies of BCIs to improve rehabilitation for patients with stroke have shown some promise, but the mechanisms by which BCIs enable recovery have been understudied. As a result, significant questions remain before meaningful clinical translation of BCIs for stroke rehabilitation can occur. Who are the patients who would optimally benefit from BCI neurorehabilitation? What is the optimal time period post-stroke for BCI training? In this proposed career development application, I will leverage a unique and ongoing clinical-research infrastructure at Providence VA Medical Center and Massachusetts General Hospital, which has recruited over 120 acute stroke patients with arm weakness in 2.5 years and followed these patients through the course of their first year of recovery with arm motor outcome measures including Fugl-Meyer and upper extremity kinematics, neuroimaging, and neurophysiology. I will directly extend this study by adding EEG- BCI arm orthosis sessions at four study time points, with the first session occurring within days of stroke. My first aim is to identify longitudinal changes in cortical functional connectivity induced by single- sessions of EEG-BCI arm orthosis training. I will investigate specific neural circuits that are strengthened by EEG-BCI training and the post-stroke time window in which circuits are most sensitive to training. My second aim is to evaluate how baseline arm motor severity and stroke neuroanatomy modulate the effects of EEG- BCI arm orthosis training on cortical functional connectivity. I will investigate the effects of arm Fugl-Meyer and structural injury to specific anatomic structures on EEG-BCI induced circuit changes. Furthermore, this project will allow me to integrate my research and clinical career into the VA system and will provide me with fundamental scientific tools in quantification of brain networks, neural engineering, and longitudinal analysis of motor performance and recovery outcomes, supported by an exceptional VA-based mentorship team. This project is (1) innovative because it directly extends a unique clinical-research infrastructure within an exceptional environment for neurotechnology and neurorestoration at Providence VAMC and MGH that, to my knowledge, is unavailable elsewhere in the world (2) impactful because the fundamental insights into the neural mechanisms of EEG-BCI therapy for arm motor neurorehabilitation gained here will advance translation of BCI neurotechnology to the clinic and (3) significant because it is the first step in VA integration of my career that will ultimately provide the opportunity for me to lead a VA team to clinically translate BCI technologies to enable maximal recovery of function and improve quality of life for Veterans after stroke.