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NeuroscienceJournal of Neurophysiology
Peer-reviewed journal article

Two ways to learn in visuomotor adaptation

Yifan Zhang, Sana Jayaswal, Nicolas SchweighoferiD

Abstract

Previous research has demonstrated significant inter-individual variability in the recruitment of the fast-explicit and slow-implicit processes during motor adaptation. In addition, we previously identified qualitative individual differences in adaptation linked to the formation and updating of new memory processes. Here, we investigated quantitative and qualitative differences in visuomotor adaptation with a design incorporating repeated learning and forgetting blocks, allowing for precise estimation of individual learning and forgetting rates in fast-slow adaptation models. Participants engaged in a two-day online visuomotor adaptation task. They first adapted to a 30-degree perturbation to eight targets in three blocks separated by short blocks of no feedback trials. Approximately 24 hours later, they performed a no-feedback retention block and a relearning block. We clustered the participants into strong and weak learners based on adaptation levels at the end of day one and fitted a fast-slow system to the adaptation data. Strong learners exhibited a strong negative correlation between the estimated slow and fast processes, which predicted 24-hour retention and savings, respectively, supporting the engagement of a fast-slow system. The pronounced individual differences in the recruitment of the two processes were attributed to wide ranges of estimated learning rates. Conversely, weak learners exhibited a positive correlation between the two estimated processes, as well as retention but no savings, supporting the engagement of a single slow system. Finally, both during baseline and adaptation, reaction times were shorter for weak learners. Our findings thus revealed two distinct ways to learn in visuomotor adaptation and highlight the necessity of considering both quantitative and qualitative individual differences in studies of motor learning.

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