The goal of our research is to understand the computational principles underlying human sensorimotor control. To examine the computations underlying sensorimotor control, we have developed a research program that uses computational techniques from machine learning, control theory and signal processing together with novel experimental methods that include robotic interfaces and virtual reality systems that allow for precise experimental control over sensory inputs and task variables (Franklin and Wolpert, 2011; Wolpert et al., 2011).
Voluntary movement is fundamental to human existence. Yet, impairments of human movement, due to stroke, degenerative disease, and developmental disorders, affects 5% of the population over their life span. To understand the underlying brain processes that control human movement, and their malfunction in disease, requires a major interdisciplinary effort using the latest scientific developments and technological tools. By providing a strong computational understanding of human sensorimotor control, our research can form the basis for developments that have implications for human health in terms of understanding disease processes and for rehabilitation programs.
