Motor learning without movement

Prediction errors guide many forms of learning, providing teaching signals that help us improve our performance. Implicit motor adaptation, for instance, is driven by sensory prediction errors (SPEs), which occur when the expected and observed consequences of a movement differ. Traditionally, SPE computation is thought to require movement execution. However, recent work suggesting that the brain generates and accounts for sensory predictions based on motor imagery or planning alone calls this assumption into question. Here, by measuring implicit adaptation during a visuomotor task, we tested whether motor planning and well-timed sensory feedback are sufficient for SPE computation. Human participants were cued to reach to a target and were, on a subset of trials, rapidly cued to withhold these movements. Errors displayed both on trials with and without movements induced single-trial implicit learning. Learning following trials without movements persisted even when movement trials had never been paired with errors, and when the direction of movement and sensory feedback trajectories were decoupled. These observations demonstrate that the brain can compute SPEs without generating overt movements, leading to the adaptation of planned movements even when they are not performed. SIGNIFICANCE STATEMENTWe are always learning from our mistakes, because the brain is constantly generating predictions and monitoring the world for any surprises, which are also referred to as "prediction errors." Whenever a prediction error occurs, the brain learns to update future predictions and be more accurate. Here, we demonstrate that the brain predicts the consequences of movements, computes prediction errors, and updates future movements, even if we subsequently decide to withhold the movement. Thus, the brain can learn to update movements that are not performed, representing a mechanism for learning based only on movement planning and sensory expectation. These findings also provide further support for the role of prediction in motor control. SIGNIFICANCE STATEMENTOur brains control aspects of our movement without our conscious awareness - allowing many of us to effortlessly pick up a glass of water or wave "hello." Here, we demonstrate that this implicit motor system can learn to refine movements that we plan but ultimately decide not to perform. Participants planned to reach to a target, and they sometimes withheld these reaches. When reaches were withheld, an animation simulating a reach that missed the target played. Afterwards, participants reached opposite the direction of the mistake without awareness of this change in their movements, indicating that the implicit motor system had learned from the animated mistake. These findings indicate that movement is not strictly necessary for motor adaptation, and that we can learn to update our actions based only on movement planning and observation of related events in the world.