|M.Sc Student||Klaiman Eldad|
|Subject||Unraveling Features of the Neural Control System that|
Generates Periodic Bimanual Coordination
|Department||Department of Electrical and Computer Engineering||Supervisor||DR. Karniel Amir|
From tying your shoes and clipping your tie to the claps at the end of a fine seminar bimanual coordination plays a major role in our daily activities. A prominent phenomenon documented and modeled in various studies is the predisposition of human coordination towards mirror symmetry in performance of bimanual rhythmic movements. This characteristic makes the acquisition and performance of bimanual tasks with complex phase relations very difficult.
The human motor control system is extremely adaptive allowing us to adjust to a multitude of scenarios such as body growth, injury or environmental changes. Adaptive control theory and the notion of internal models were successfully employed in the arenas of grip force modulation, reaching movements and adaptation to force perturbations. However, in the context of bimanual coordination these tools have never been employed and the existing computational models address only the steady states of the behavior.
We have conducted simple experiments in which subjects were exposed to an altered visual feedback and trained to perform a complex bimanual tapping task (non-harmonic polyrhythm). The experimental results revealed learning curves, after-effects and washout, which are clear cut evidence for the formation of internal models. We introduce minimal, physiologically plausible, neural model which combines feedback and adaptation in the control process and which is able to reproduce key phenomena of bimanual coordination and adaptation.
The application of internal models and adaptive control to paradigms in bimanual coordination may open new horizons for the study of internal models in the context of various forms of natural motor behaviors.