Taking aim at the perceptual side of motor learning: Exploring how explicit and implicit learning encode perceptual error information through depth vision
Motor learning in visuomotor adaptation tasks results from both explicit and implicit processes, each responding differently to an error signal. While the motor output side of these processes is extensively studied, their visual input side is relatively unknown. We investigated if and how depth perception affects the computation of error information by explicit and implicit motor learning. Two groups of participants threw virtual darts at a virtual dartboard while receiving perturbed endpoint feedback. The Delayed group was allowed to re-aim and their feedback was delayed to emphasize explicit learning, while the Clamped group received clamped cursor feedback which they were told to ignore, and continued to aim straight at the target to emphasize implicit adaptation. Both groups played this game in a highly detailed virtual environment (Depth condition) and in an empty environment (No-Depth condition). The Delayed group showed an increase in error sensitivity under Depth relative to No-Depth conditions. In contrast, the Clamped group adapted to the same degree under both conditions. The movement kinematics of the Delayed participants also changed under the Depth condition, consistent with the target appearing more distant, unlike the Clamped group. A comparison of the Delayed behavioral data with a perceptual task from the same individuals showed that the effect of the Depth condition on the re-aiming direction was consistent with an increase in the scaling of the error distance and size. These findings suggest that explicit and implicit learning processes may rely on different sources of perceptual information. New & NoteworthyWe leveraged a classic sensorimotor adaptation task to perform a first systematic assessment of the role of perceptual cues in the estimation of an error signal in the 3D space during motor learning. We crossed two conditions presenting different amounts of depth information, with two manipulations emphasizing explicit and implicit learning processes. Explicit learning responded to the visual conditions, consistent with perceptual reports, while implicit learning appeared to be independent of them.