@article{182251, author = {Carlo Campagnoli and Fulvio Domini and Jordan A. Taylor}, title = {Taking aim at the perceptual side of motor learning: Exploring how explicit and implicit learning encode perceptual error information through depth vision}, abstract = {

Motor learning in visuomotor adaptation tasks results from both explicit and implicit processes, each responding differently to an error signal. Although the motor output side of these processes has been extensively studied, the 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 made reaching movements to bring a virtual cursor to a target in the frontoparallel plane. The Delayed group was allowed to reaim and their feedback was delayed to emphasize explicit learning, whereas the camped group received task-irrelevant clamped cursor feedback and continued to aim straight at the target to emphasize implicit adapta- tion. Both groups played this game in a highly detailed virtual environment (depth condition), leveraging a cover task of playing darts in a virtual tavern, and in an empty environment (no-depth condition). The delayed group showed an increase in error sen- sitivity under depth relative to no-depth. 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 indi- viduals showed that the greater reaiming in the depth condition was consistent with an increase in the scaling of the error dis- tance and size. These findings suggest that explicit and implicit learning processes may rely on different sources of perceptual information.

}, year = {2021}, journal = {J Neurophysiol}, volume = {126}, pages = {413-426}, doi = {10.1152/jn.00153.2021}, language = {eng}, }