Denise Jennifer Berger

This paper presents a computational model that learns redundant muscle activity patterns in novel sensorimotor tasks through trial-by-trial adaptation of muscle synergies and their recruitment coefficients.

This study investigates the ability to control muscle activation in the null-space of the wrist system for movement augmentation, finding limitations in null-space control but capability in concurrent force and co-contraction control.

The paper shows that task space exploration improves adaptation after incompatible virtual surgeries by enabling learning of new muscle synergies.