Automatic, but not autonomous: Implicit adaptation is modulated by goal-directed attentional demands

Abstract

Implicit adaptation recalibrates movements based on sensory prediction errors. It is often characterized as automatic and resource-independent, suggesting that it is insulated from cognitive influence. Here, we asked whether implicit adaptation is sensitive to goal-directed attentional demands imposed by a concurrent visual task. Across two experiments, we used clamped visual feedback to measure implicit adaptation while human adults (49 female, 23 male) monitored a rapidly changing visual stream for targets. In Experiment 1, participants performing the visual task showed modest early enhancement in implicit adaptation relative to a single-task control condition. In Experiment 2, adding response-contingent feedback to the visual task led to stronger and more sustained enhancement. Visual task accuracy and implicit adaptation were uncorrelated, arguing against resource competition. Model-based analyses revealed elevated error sensitivity under dual-task conditions, with individual differences reflecting an inverse relationship between error sensitivity and retention. These patterns are compatible with arousal-mediated modulation of cerebellar error processing and hierarchical models of cerebellar learning. Together, these findings suggest that implicit adaptation is automatic but not autonomous: while it operates outside voluntary control, it appears open to the physiological states in which errors are experienced.

Significance Statement Implicit adaptation helps us fine-tune movements using sensory feedback, keeping our actions calibrated as our body or the environment changes. This learning process operates automatically, meaning we cannot control it even if we try. But does that mean it is completely independent of what else we are doing? We found that when people performed a visual monitoring task at the same time as a reaching task, they adapted more, not less. This enhancement was strongest when the visual task included feedback that sustained engagement. These findings suggest that automatic learning is shaped not only by the errors we experience, but also by the physiological context in which they occur.