Tracking fast unpredictable movements is a valuable skill, applicable in many situations. In the animal kingdom, the context includes the action of a predator chasing its prey that is running and dodging at high speeds, like a cheetah chasing a gazelle. The sensorimotor control system (SCS) is responsible for such actions and its performance clearly depends on the computing power of neurons, delays between brain and muscles, and the dynamics of muscles involved (Figure above). Despite these obvious factors that set the limits on how fast an animal can track a moving object, tracking performance of the SCS and its dependence on neural computing, delays, and muscle dynamics have not been explicitly quantified. Our lab, in collaboration with Munther Dahleh (MIT), is building upon new theory developed using feedback control principles and an appropriately simplified model of the sensorimotor control system (SCS) to identify how neural computing, delays, and muscles interact during the generation of fast movements. Therefore if one component is compromised, we can take advantage of the other components to restore motor performance with assistive neuroprosthetic devices. For example, if the primary motor cortex is compromised due to disease or damage, we can manipulate muscle dynamics by adding the necessary compensatory forces to restore motor performance, and more importantly fast and agile movements. Just how one should compensate will be informed by our SCS model and theory.
Our research objectives are to first parameterize the three major factors limiting fast movements and to derive how these parameters must interact to achieve tracking of fast movements in the SCS. Then, the parameterization and quantified interactions will be tested experimentally in nonhuman primates, in collaboration with Marc Schieber, through manipulation of (i) neural computing power, (ii) transmission delays, and (iii) muscle dynamics. If discrepancies emerge between experiments and theory, the SCS model and theory will be modified to explain observed data. Finally, the theoretical model of interactions required to achieve tracking of fast movements will be exploited to apply compensation to account for degradation of some parameters by “boosting” others (in collaboration with Amy Bastian). More specifically, we will design assistive neuroprosthetic devices for primates having compromised neural real estate to restore performance of fast movements.
This work is funded by:
- NIH NINDS R01