Motion capture is widely used for character animation. One of the major challenges of this technique is how to modify the captured motion in plausible ways. Previous work has focused on transformations based on kinematics and dynamics, but has not explicitly taken into account the emerging knowledge of how humans control their movement. In this paper, we show how this can be done using a simple human neuromuscular control model. Our model of muscle forces includes a feedforward term, and low-gain passive feedback. The feedforward component is calculated from motion capture data using inverse dynamics. The feedback component generates reaction forces to unexpected external disturbances. The perturbed animation is then resynthesized using forward dynamics. This allows us to create animation where the character reacts to unexpected external forces in a natural way (e.g.,when the character is hit by a flying object), and still retain the quality of the captured motions. This technique is useful for applications such as interactive sports video games.