CAREER: Neural Mechanisms Underlying a Neuroprosthetic Skill

脑机接口（bmi）可以帮助从脑损伤中恢复，比如中风。bmi指数也是了解健康和受伤大脑学习能力的有力研究工具。众所周知，睡眠在学习和记忆中起着至关重要的作用，最近的研究表明，睡眠是学习与脑机界面互动的重要因素。这个NSF教师早期职业发展（Career）项目为一个研究和教育项目奠定了基础，该项目将发现健康和中风损伤的大脑中与睡眠相关的重组之间的联系，这有助于学习脑机接口技能。它还将测试刺激睡眠的某些阶段是否能促进学习。对神经假肢技能学习背后的科学的更好理解，可以为中风如何影响大脑与睡眠相关的学习提供新的见解。这项工作的结果可以用来帮助为中风患者设计以睡眠为中心的康复计划和BMI系统。脑机接口提供了一种强大的技术，将神经系统的计算能力与人工电子系统的计算能力结合在一起。BMI学习有助于探索大脑的感觉运动可塑性，最近的工作揭示了运动皮层中的离线过程，这些过程在学习神经假肢运动任务时导致表现提高。此外，运动皮质刺激和小脑深核刺激都显示出促进中风后运动恢复的希望。然而，这些刺激是在清醒时应用的。这些区域是否存在协调的离线睡眠相关处理，以及这种离线活动是否可以优化以促进神经假肢技能的学习，这些都尚未得到验证。本研究在NSF CAREER项目下进行，旨在描述啮齿动物在学习神经假肢任务时皮质-小脑区域的离线过程，以了解这些区域的BMI学习的神经基础。研究人员将在健康和中风受伤的大鼠身上进行研究，重点关注有助于学习BMI技能的睡眠过程。研究人员将采用系统级的方法：(1)表征睡眠阶段和皮质-小脑系统的神经处理过程，这有助于在完整和中风损伤的大脑中巩固神经假肢技能；（ii）测试在睡眠中增强这些区域的神经过程是否可以用于增强神经假肢技能的学习和恢复。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Brain-machine interfaces (BMIs) can aid recovery from brain injuries, such as stroke. BMIs are also powerful research tools for understanding learning in healthy and injured brains. Sleep is known to play a crucial role in learning and memory, and recent work has shown that sleep is a vital factor in learning to interact with a brain-machine interface. This NSF Faculty Early Career Development (CAREER) project lays the foundation for a research and education program that will discover the links between sleep-associated reorganization in healthy and stroke-injured brains that help in learning a brain-machine interface skill. It will also test whether stimulating certain phases of sleep can boost learning. An improved understanding of the science behind neuroprosthetic skill learning can lead to new insights into how stroke impacts the brain’s sleep-related learning. The results of this work could be used to help design sleep-focused rehabilitation programs and BMI systems for those suffering from stroke. Brain-machine interfaces offer a powerful technology that merges the computational power of nervous systems with that of artificial electronic systems. BMI learning lends itself to probing sensorimotor plasticity in the brain, and recent work has revealed offline processes in the motor cortex that lead to performance gains while learning a neuroprosthetic motor task. Furthermore, motor cortical stimulation and cerebellar deep nuclei stimulation have both shown promise in promoting motor recovery post-stroke. However, these stimulations have been applied during awake periods. Whether there is any coordinated offline sleep-related processing in these regions and whether such offline activity can be optimized to promote learning of a neuroprosthetic skill remains untested. The research performed under this NSF CAREER project aims to delineate the offline processes in cortico-cerebellar areas of rodents during the learning of a neuroprosthetic task, to understand the neural basis of BMI learning in these regions. The investigators will perform studies in healthy and stroke-injured rats and focus on sleep processing that contributes to learning a BMI skill. The investigators will take a systems-level approach to: (i) characterize the sleep stages and neural processing in cortico-cerebellar ensembles that help in consolidating a neuroprosthetic skill in the intact and the stroke-injured brain; and (ii) test if augmentation of neural processes during sleep in these regions can be used to enhance learning and recovery of a neuroprosthetic skill.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.