title: Prediction precedes control in motor learning.
abstract: Skilled motor behavior relies on the brain learning both to control the body and predict the consequences of this control. Prediction turns motor commands into expected sensory consequences, whereas control turns desired consequences into motor commands. To capture this symmetry, the neural processes underlying prediction and control are termed the forward and inverse internal models, respectively. Here, we investigate how these two fundamental processes are related during motor learning. We used an object manipulation task in which subjects learned to move a hand-held object with novel dynamic properties along a prescribed path. We independently and simultaneously measured subjects' ability to control their actions and to predict their consequences. We found different time courses for predictor and controller learning, with prediction being learned far more rapidly than control. In early stages of manipulating the object, subjects could predict the consequences of their actions, as measured by the grip force they used to grasp the object, but could not generate appropriate actions for control, as measured by their hand trajectory. As predicted by several recent theoretical models of sensorimotor control, our results indicate that people can learn to predict the consequences of their actions before they can learn to control their actions.
authors.affiliation: Department of Psychology, Centre for Neuroscience Studies, Queen's University, K7L 3N6, Kingston, Ontario, Canada.
authors.forename: J Randall
authors.initials: JR
authors.lastname: Flanagan
authors.forename: Philipp
authors.initials: P
authors.lastname: Vetter
authors.forename: Roland S
authors.initials: RS
authors.lastname: Johansson
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Wolpert
mesh_terms: D055592:Biophysical Phenomena; D001703:Biophysics; D006225:Hand; D018737:Hand Strength / Q000502:physiology; D006801:Humans; D007858:Learning / Q000502:physiology*; D009048:Motor Skills / Q000502:physiology*