Statistical learning facilitates the strategic use of attentional control. Academic Article uri icon

abstract

  • A growing body of research suggests that observers rely on a variety of suboptimal strategies when searching for objects. However, real-world environments contain a variety of statistical regularities that enable more efficient processing of information. In the present study, we examined whether statistical learning can influence the strategic use of attentional control using a modified version of the adaptive choice visual search task. Participants searched through an array of colored squares and identified a digit located within a red or blue target square. Each trial contained both a red and a blue target, and participants were free to choose which color to search for. On each trial, more squares were presented in one color than the other color. Thus, the optimal strategy was to search for the color with the fewest squares. Critically, one color was the optimal color on 75% of trials, while the other color was the optimal color on the remaining 25% of trials. Participants were faster to identify targets and made a larger proportion of optimal choices when the high-probability optimal color was optimal. Thus, statistical learning facilitated both search for the targets and the optimal choice of attentional control settings. These effects persisted when the color contingencies were equated, suggesting that these findings were not simply due to intertrial priming. Moreover, participants were not slower to identify targets when the high-probability optimal color appeared as a distractor, suggesting that these findings were not due to attentional capture by this color. Together, these findings suggest that statistical learning can facilitate the strategic use of attentional control by biasing which features observers choose to search for.

published proceedings

  • Cognition

altmetric score

  • 2.35

author list (cited authors)

  • Clement, A., & Anderson, B. A.

citation count

  • 1

complete list of authors

  • Clement, Andrew||Anderson, Brian A

publication date

  • October 2023