Performance Limitations in Sensorimotor Control: Trade-offs between Neural Computing and Accuracy in Tracking Fast Movements [article]

Shreya Saxena, Sridevi V. Sarma, Munther Dahleh
2018 bioRxiv   pre-print
The ability to move fast and accurately track moving objects is fundamentally constrained by the biophysics of neurons and dynamics of the muscles involved. Yet, the corresponding tradeoffs between these factors and tracking motor commands have not been rigorously quantified. We use feedback control principles to identify performance limitations of the sensorimotor control system (SCS) to track fast periodic movements. We show that (i) linear models of the SCS fail to predict known undesirable
more » ... known undesirable phenomena, including skipped cycles, overshoot and undershoot, produced when tracking signals in the "fast regime", while non-linear pulsatile control models can predict such undesirable phenomena, and (ii) tools from nonlinear control theory allow us to characterize fundamental limitations in this fast regime. Using a validated and tractable nonlinear model of the SCS, we derive an analytical upper bound on frequencies that the SCS can reliably track before producing such undesirable phenomena as a function of the neurons' computational complexity and muscle dynamics. The performance limitations derived here have important implications in sensorimotor control.For example, if primary motor cortex is compromised due to disease or damage, the theory suggests ways to manipulate muscle dynamics by adding the necessary compensatory forces using an assistive neuroprosthetic device to restore motor performance, and more importantly fast and agile movements. Just how one should compensate can be informed by our SCS model and the theory developed in this paper.
doi:10.1101/464230 fatcat:f3kdggxajrh27hwfy6uscbdply