Anticipatory gaze in a reaching-and-grasping task when target movement direction is uncertain: evidence of statistical learning

Successful goal-directed actions in dynamic environments depend on the brain's ability to implicitly learn probabilistic regularities, enabling anticipatory behaviors and reducing cognitive demands. Humans can utilize visual and non-visual aspects about the target to predict its direction. We investigated whether individuals could implicitly exploit a target's directional movement history during a grasping task to predict its future direction, under uncertain conditions, lacking any clues about the target's eventual movement. In each trial, a target appeared in the middle of the screen, remained stationary for 2.50 s, then translated horizontally toward the left or the right. Participants first completed a non-biased block of trials, before completing either two rightward or leftward biased blocks. Upon exposure to the biased blocks, participants' average gaze shifted toward the direction of the eventual movement of the target prior to its movement, suggesting an adaptation in gaze strategy as the experiment progressed. Later trials showed a greater distance from the target's horizontal midline compared to earlier trials. Furthermore, anticipatory behavior facilitated more efficient reactive gaze adjustments once the target began moving, enabling participants to align their gaze more closely with the target and thus reducing cognitive load. This study highlights the visuomotor system's ability to implicitly use probabilistic patterns, enhancing anticipatory and reactive gaze strategies that improve the execution of goal-directed actions.

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Publication Details

Journal
Frontiers in Psychology
Published
2026-02-16
DOI
https://doi.org/10.3389/fpsyg.2026.1625415
Primary Topic
Motor Control and Adaptation
Type
article
Field-Weighted Citation Impact
0.00

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article

Anticipatory gaze in a reaching-and-grasping task when target movement direction is uncertain: evidence of statistical learning

Jonathan J. Marotta, Youssef G Ekladuce, Ryan W. Langridge
Frontiers in Psychology
Motor Control and Adaptation
article

Anticipatory gaze in a reaching-and-grasping task when target movement direction is uncertain: evidence of statistical learning

Jonathan J. Marotta, Youssef G Ekladuce, Ryan W. Langridge
article en

Abstract

Successful goal-directed actions in dynamic environments depend on the brain's ability to implicitly learn probabilistic regularities, enabling anticipatory behaviors and reducing cognitive demands. Humans can utilize visual and non-visual aspects about the target to predict its direction. We investigated whether individuals could implicitly exploit a target's directional movement history during a grasping task to predict its future direction, under uncertain conditions, lacking any clues about the target's eventual movement. In each trial, a target appeared in the middle of the screen, remained stationary for 2.50 s, then translated horizontally toward the left or the right. Participants first completed a non-biased block of trials, before completing either two rightward or leftward biased blocks. Upon exposure to the biased blocks, participants' average gaze shifted toward the direction of the eventual movement of the target prior to its movement, suggesting an adaptation in gaze strategy as the experiment progressed. Later trials showed a greater distance from the target's horizontal midline compared to earlier trials. Furthermore, anticipatory behavior facilitated more efficient reactive gaze adjustments once the target began moving, enabling participants to align their gaze more closely with the target and thus reducing cognitive load. This study highlights the visuomotor system's ability to implicitly use probabilistic patterns, enhancing anticipatory and reactive gaze strategies that improve the execution of goal-directed actions.

Frontiers in PsychologyVol. 17
University of Manitoba (CA)
Research Manitoba, Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 55%
Motor Control and Adaptation
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