CAREER: Mechanics and Control of Brain-Machine Interface Systems

该学院早期职业发展(Career)项目的研究目标是推导出改善脑机接口性能的人类运动控制和学习模型。通过直接测量大脑活动，这些接口使感觉-运动功能受损的人能够单靠思维控制假肢和其他假肢设备。受人类运动控制基于运动命令的离散内部表征以及行为运动恢复类似于函数语言习得的证据的启发，该方法将专注于构建统计语言模型，以允许对运动程序进行增量规范。在反馈信息理论和分散控制的框架下，这种方法将导致为假肢设备设计更好地反映用户意图的反馈控制系统。如果成功，这项研究将为恢复感觉-运动功能提供新的机会，潜在地改善因截肢、脊髓损伤和中风等疾病而致残的人的生活质量。这项研究还可能导致更好地理解中枢神经系统如何与外围生物力学相互作用来控制动作和感知，这反过来对于理解更高的认知功能并最终对大脑进行反向工程是必不可少的。作为补充教育计划的一部分，PI将促进小学生的互动演示，共同指导为期一周的高中生暑期研究所，并开发和评估课程，为本科生和研究生进行整合系统工程和神经科学的研究做准备。

The research objective of this Faculty Early Career Development (CAREER) project is to derive models of human motor control and learning that improve the performance of brain-machine interfaces. Through direct measurement of brain activity, these interfaces enable people with impaired sensory-motor function to control artificial limbs and other prosthetic devices by thought alone. Inspired by evidence that human motor control is based on a discrete internal representation of motor commands and that behavioral motor recovery is similar to the acquisition of functional language, the method of approach will focus on the construction of statistical language models that allow incremental specification of motor programs. Grounded within the framework of feedback information theory and decentralized control, this approach will result in the design of feedback control systems for prosthetic devices that better reflect user intent.If successful, this research will provide new opportunities to restore sensory-motor function, potentially improving the quality of life for people with disability due to conditions like amputation, spinal cord injury, and stroke. This research may also result in a better understanding of how the central nervous system interacts with peripheral biomechanics to control action and perception, which in turn is essential for understanding higher cognitive function and ultimately for reverse-engineering the brain. As part of a complementary educational program, the PI will facilitate interactive demonstrations for elementary school students, co-direct a week-long summer institute for high school students, and develop and assess courses preparing undergraduate and graduate students for research that integrates systems engineering and neuroscience.