Models of Motor Learning Generalization.

This study used evidence from trial-by-trial errors to understand how humans can generalize what they learn across different movement directions while reaching. We trained 15 healthy subjects to reach in six directions in the presence of challenging visuomotor distortions. We then tested a number of candidate models suggested by the literature of how the brain might use error to improve performance. Our cross-validated results point to a discrete affine model whose generalization, or influence of practice in one direction to neighboring directions, is reduced nearly to zero by 60 degrees away, and the subjects learned 6.25 times more from the error that was observed at a movement direction than neighboring directions.