A large body of research has led to statistical models showing how movement velocity is encoded in the motor cortex. These models have been validated by the control of neural prosthetics which restore natural arm and hand movement to paralyzed individuals. However, forces also need to be controlled in harmony with motion when interacting with objects. While many studies have examined force and motion separately, 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 poses severe limitations on our understanding of the control 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 and how the impedance of the hand is signaled during object interaction. 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.
Making movements to effect changes in our surroundings has received widespread attention as a fundamental factor in cognitive theories of mind, which underscore motor control as an essential component of the human experience. In recent years, much has been discovered about how the motor cortex enables reaching movements, but we understand very little about the control used as we interact with objects such as tools. Results of this study could provide valuable insight into the fundamental principles of this control and advance our understanding of the way we act on our surroundings. The decoding algorithms developed in this works will be used for neural prostheses that restore the ability of paralyzed subjects to manipulate objects in their surroundings.
