Monday April 29, 2019 at 4:00 PM in Yost 306

Speaker: Yangyang Wang

Abstract

Central pattern generators (CPGs) are neural networks that are intrinsically capable of producing rhythmic patterns of neural activity without receiving sensory inputs, and are adaptable to sensory feedback to produce robust motor behaviors such as breathing, walking, and swallowing. The mechanism underlying robust motor control mediated by the sensory feedback would be to adjust both the timing and the path of neuromechanical trajectories that can have hard boundary conditions. Motivated by this, we generalize variational and phase response analysis developed for stable limit cycle systems to the piecewise smooth limit cycle systems with hard boundaries. These analyses are then applied to a piecewise smooth neuromechanical model to uncover the mechanism of the robust sensory feedback control, in comparison with experimental data from the food-swallowing behavior in the sea slug Aplysia.