CAREER: Consolidation of Motor Memory for Brain-Machine Interfaces

CarmenaBrain-Machine接口技术有可能改善数百万因中枢神经系统病变或其他神经系统疾病而瘫痪的患者的生活质量。我们之前的发现表明，即使在没有明显的手臂动作的情况下，猴子也可以通过使用视觉反馈通过脑机接口控制机器人手臂来学习接触和抓住虚拟物体。这项提议旨在通过以模仿技能获得和运动控制的自然过程的方式毫不费力地回忆运动记忆，使该领域向神经假体设备的最终控制更近一步。这一目标将通过以下具体目标来实现：1)研究假体运动记忆的形成和稳定；2)研究假体功能的神经元-行为关系。该项目将为了解大脑如何控制非实体设备的运动奠定科学基础，并将推动下一代神经假体的开发，这些假体将恢复数百万神经受损患者的运动功能。这项建议的强大教育部分依赖于脑机接口，作为科学和工程跨学科教育的理想平台。拟议的措施旨在解决目前国家理工科专业人才短缺的问题，这可能会对经济增长产生严重的负面影响。这将通过一个辅导方案来实现，该方案旨在增加进入工程学职业生涯的人数不足的女学生人数。该计划还将通过教学、协作、数据共享、研讨会和教程，让本科生和研究生、学术界和工业界参与脑机接口研究。

0954243CarmenaBrain-machine interface technology has the potential of improving the quality of life for millions of patients suffering from paralysis due to lesions of the central nervous system or other neurological disorders. Our previous findings showed that monkeys can learn to reach and grasp virtual objects by controlling a robot arm through a brain-machine interface using visual feedback, even in the absence of overt arm movements. This proposal aims at bringing the field one step closer towards the ultimate control of neuroprosthetic devices through an effortless recall of a motor memory in a manner that mimics the natural process of skill acquisition and motor control. This goal will be pursued through the following specific aims: 1) To investigate the formation and stabilization of a prosthetic motor memory; 2) To investigate the neuron-behavior relationship for prosthetic function. This project will establish a scientific basis for understanding how the brain controls movement of disembodied devices, and will drive the development of the next generation of neural prosthetics that will restore motor function in millions of neurologically impaired patients. The strong educational component of this proposal relies on brain-machine interfaces as an ideal platform for interdisciplinary education in science and engineering. The proposed efforts aim to address the nations current talent shortage of science and engineering majors which could have a severe negative impact on economic growth. This will be pursued through a mentoring program aimed at increasing the number of underrepresented and women students entering careers in engineering. The program will also involve undergraduate and graduate students, academics, and the industrial community in brain-machine interface research through teaching, collaborations, data sharing, workshops and tutorials.