Motor cortical signaling of impedance during manipulation

项目摘要 大量的研究已经产生了统计模型，显示了运动速度是如何在马达中编码的 大脑皮层。然而，当与物体交互时，力也需要与运动和谐地控制，并且 很少有人把研究重点放在发动机系统如何协调两者。同步变分 力和运动的关系被并入阻抗的定义中。我们目前的神经模型不能描述 阻抗编码，这限制了我们对物体交互的理解，这是人类的一个重要方面 行为。提出的研究将开发物体运动皮层阻抗编码的新模型 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 先进的阻抗控制理论，由电机系统用来产生精确的物体位移 对手所施加的力的反应。这项研究将施瓦茨博士的专业知识联系在一起 神经生理学和霍根博士在机器人控制方面的研究。猴子受试者会用真实和虚拟的方式执行任务 自然鼓励使用阻抗控制的工具。我们将记录运动皮质的活动 并发展出新的数学模型来描述神经之间的关系 活动和力，运动和阻抗。肌电记录的结果，关节角度 测量和扭矩计算，以及神经模型将被用来更好地理解 阻抗是在肌肉和关节的水平上调节的。伸展反射对阻抗的贡献将是 研究并与从运动皮质中解码的预测阻抗信号进行了比较。这项工作有希望 为了扩大我们对支配我们使用手臂和手的方式的神经控制原理的理解 与我们周围的环境互动。这些原则可以用来建立认知过程的新理论。 用来预测和影响我们周围世界的变化。同时，阐明了神经和 强相互作用的机械细节将导致新的康复和神经假体方法 瘫痪。

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.