No abstract

The human sensorimotor system is sensitive to both limb-related prediction errors and task-related performance errors. Prediction error signals are believed to drive implicit refinements to motor plans. However, an understanding of the mechanisms that performance errors stimulate has remained unclear largely because their effects have not been probed in isolation from prediction errors. Diverging from past work, we induced performance errors independent of prediction errors by shifting the location of a reach target but keeping the intended and actual kinematic consequences of the motion matched. Our first two experiments revealed that rather than implicit learning, motor adjustments in response to performance errors reflect the use of deliberative, volitional strategies. Our third experiment revealed a potential dissociation of performance-error-driven strategies based on error size. Specifically, behavioral changes following large errors were consistent with goal-directed or model-based control, known to be supported by connections between prefrontal cortex and associative striatum. In contrast, motor changes following smaller performance errors carried signatures of model-free stimulus-response learning, of the kind underpinned by pathways between motor cortical areas and sensorimotor striatum. Across all experiments, we also found remarkably faster re-learning, advocating that such "savings" is associated with retrieval of previously learned strategic error compensation and may not require a history of exposure to limbrelated errors. 3 SIGNIFICANCE STATEMENTHumans adjust their actions if they do not produce desired limb-related sensory consequences or task-related outcomes. We probed whether task-related performance errors induce implicit changes to motor plans at all, or simply trigger the deliberate selection of different actions. We induced performance errors in isolation, and found that they were compensated entirely via intentional, strategic mechanisms consistent with improved action selection. Strategies also appeared to be sensitive to error size, and transitioned from stimulus-response associative behavior to goaldirected control as error magnitude increased. Across all experiments, we also found faster re-learning or "savings", substantiating the view that savings is associated with strategy-use, and does not depend on experience of limb-related prediction errors that bring about implicit adjustments to action plans.