Implicit reward-based motor learning

Abstract

Binary feedback, providing information solely about task success or failure, can be sufficient to drive motor learning. While binary feedback can induce explicit adjustments in movement strategy, it remains unclear if this type of feedback also induces implicit learning. We examined this question in a center-out reaching task by gradually moving an invisible reward zone away from a visual target to a final rotation of 7.5° or 25° in a between-group design. Participants received binary feedback, indicating if the movement intersected the reward zone. By the end of the training, both groups modified their reach angle by about 95% of the rotation. We quantified implicit learning by measuring performance in a subsequent no-feedback aftereffect phase, in which participants were told to forgo any adopted movement strategies and reach directly to the visual target. The results showed a small, but robust (2–3°) aftereffect in both groups, highlighting that binary feedback elicits implicit learning. Notably, for both groups, reaches to two flanking generalization targets were biased in the same direction as the aftereffect. This pattern is at odds with the hypothesis that implicit learning is a form of use-dependent learning. Rather, the results suggest that binary feedback can be sufficient to recalibrate a sensorimotor map.