Use-dependent learning biases the initial state but not the learning dynamics of implicit adaptation

Motor adaptation arises from multiple learning mechanisms, including use-dependent learning (UDL) driven by repetition and implicit error-based learning (EBL) driven by motor prediction errors. Although both mechanisms contribute implicitly to shaping movement execution, whether these two mechanisms interact remains unclear. The present study used an error-clamp (EC) task to isolate implicit EBL and directly examined whether UDL affects subsequent implicit adaptation. Participants first performed extensive single-target repetitive reaches to induce use-dependent biases and then immediately transitioned to an EC task. We manipulated whether the UDL bias was aligned with, opposed to, or neutral toward the to-be-adapted direction in three separate groups of participants. Results demonstrate that UDL robustly shifted the initial state of adaptation, but did not alter the learning dynamics: all groups showed comparable trial-by-trial adaptation and converged to similar asymptotic levels despite their different initial states. These findings support an independent rather than an interactive relationship between UDL and implicit EBL, highlighting that execution-level motor learning components are additive.