Motor cortical signaling of impedance during manipulation

操纵过程中运动皮层阻抗信号

• 批准号: 10362744
• 负责人: ANDREW B. SCHWARTZ
• 金额: $ 54.14万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10362744
• 关键词: 3-Dimensional; Acceleration; Algorithms; Behavior; Collaborations; Complex; Data; Dimensions; Electromyography; Environment; Feedback; Financial compensation; Hand; Human; Isometric Exercise; Joints; Knowledge; Limb structure; Measurement; Measures; Mechanics; Modeling; Monitor; Monkeys; Motion; Motor; Motor Activity; Motor Cortex; Movement; Muscle; Neurons; Paralysed; Pattern; Population; Primates; Reaction; Reflex action; Rehabilitation therapy; Research; Research Personnel; Resistance; Robot; Sampling; Series; Signal Transduction; Statistical Models; Structure; System; Testing; Time; To specify; Torque; Variant; Virtual Tool; Viscosity; Work; arm; base; cognitive process; control theory; design; electric impedance; insight; interest; kinematics; mathematical model; motor control; multidisciplinary; neural correlate; neural model; neural prosthesis; neurophysiology; neuroregulation; nonhuman primate; novel; object motion; operation; prosthesis wearer; relating to nervous system; response; robot control; skeletal; stretch reflex; theories; tool; two-dimensional; virtual

Project Summary A large body of research has led to statistical models showing how movement velocity is encoded in the motor cortex. However, forces also need to be controlled in harmony with motion when interacting with objects and research has rarely focused on how the motor system coordinates both together. The simultaneous variation of force and motion is incorporated in the definition of impedance. Our current neural models do not describe impedance encoding, which limits our understanding of object interaction, an important aspect of human behavior. The proposed research will develop new models of motor cortical impedance encoding during object interaction. Using these new models to decode ongoing impedance signaling, we will substantiate an advanced theory of impedance control used by the motor system to produce accurate object displacement in response to the forces applied by the hand. This research bridges the expertise of Dr. Schwartz in neurophysiology and of Dr. Hogan in robot control. Monkey subjects will perform tasks with real and virtual tools that naturally encourage the use of impedance control. We will record the activity of motor cortical neurons during these tasks and develop new mathematical models to describe the relation between neural activity and force, motion and impedance. Results from electromyography recordings, joint angle measurements and torque calculations, together with the neural models, will be used to better understand how impedance is regulated at the level of muscles and joints. Contributions of stretch reflexes to impedance will be studied and compared to the predictive impedance signaling decoded from motor cortex. This work promises to extend our understanding of the neural control principles governing the way we use our arms and hands to interact with our surroundings. These principles can be used to build new theories of the cognitive processes used to predict and effect changes in the world around us. At the same time, elucidation of the neural and mechanical details of forceful interaction will lead to new rehabilitative and neural prosthetic approaches to paralysis.

项目摘要 大量的研究已经导致统计模型显示运动速度是如何在运动中编码的 皮层然而，当与物体相互作用时，力也需要与运动协调地控制， 研究很少集中在运动系统如何协调两者。同时变异 力和运动的平衡被包含在阻抗的定义中。我们目前的神经模型没有描述 阻抗编码，这限制了我们对物体相互作用的理解，而物体相互作用是人类行为的一个重要方面。 行为该研究将为开发运动皮层阻抗编码的新模型提供理论基础。 互动使用这些新模型来解码正在进行的阻抗信号，我们将证实一个 先进的阻抗控制理论，用于电机系统产生精确的物体位移， 对手施加的力的反应。这项研究将施瓦茨博士的专业知识与 神经生理学和霍根博士的机器人控制。猴子受试者会用真实的和虚拟的 自然鼓励使用阻抗控制的工具。我们将记录运动皮层的活动 神经元在这些任务中的作用，并开发新的数学模型来描述神经元之间的关系。 活动和力，运动和阻抗。肌电图记录结果，关节角度 测量和扭矩计算，以及神经模型，将用于更好地了解如何 在肌肉和关节的水平上调节阻抗。牵张反射对阻抗的贡献将是 研究并与从运动皮层解码的预测阻抗信号进行比较。这项工作承诺 扩展我们对神经控制原理的理解，这些原理支配着我们使用手臂和手的方式， 与我们的周围环境互动。这些原则可以用来建立新的认知过程理论 用来预测和影响我们周围世界的变化。同时，阐明了神经和 强有力的相互作用的机械细节将导致新的康复和神经修复方法， 瘫痪