Behavioral Benefits of Sensorimotor Predictions: Directing Attention to Maximize Informational Gain During Motor Learning

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BrandTheresa-2026-05-12.pdf (5.96 MB)

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2026-01

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DOI:
https://doi.org/10.22029/jlupub-20910

Abstract

Humans internally predict the consequences of their own motor actions using so-called forward models (e.g., Anguera et al., 2009; Flanagan & Wing, 1997; Maurer et al., 2015; Wolpert, 1997). These models simulate the input-output relationship of the musculoskeletal system by integrating sensory information about the current state of the body and the environment with copies of motor commands (Jordan & Rumelhart, 1992; Kawato, 1999; Miall & Wolpert, 1996). The present dissertation investigates functional benefits of such predictive processing, focusing on how sensorimotor predictions shape visual information uptake during motor learning. Specifically, it examines whether sensorimotor predictions direct visual attention toward spatial locations in the environment that are critical for evaluating movement outcomes and adjusting subsequent actions. To address this research question, three consecutive studies were conducted in which eye movements were recorded while participants performed a semi-virtual, goal-directed throwing task. Study I showed that sensorimotor predictions can direct gaze toward predicted action effects. The high informational value of these predictively chosen fixation locations for feedback processing was expressed by a systematic modulation of fixation durations as a function of the movement outcome. Study II demonstrated that the relevance of outcomerelated information is dynamically weighted by both outcome history and the predicted result of a current trial, supporting efficient allocation of attentional resources when multiple gaze targets compete for attention. The comparison of prediction-based top-down attentional mechanisms with salience-driven bottom-up influences in Study III suggests that, with sufficient motor expertise, responsiveness to salient distractors can be selectively modulated in feedback-critical situations. Together, these findings show that during movement execution, gaze can be directed predictively toward information relevant for learning. It can be assumed that this predictive allocation likely ensures that the necessary information for evaluating outcomes and correcting errors is gathered efficiently, particularly in time-critical situations.

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