September 2021
Volume 21, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2021
Generalization of attentional control strategies across distinct tasks
Author Affiliations & Notes
  • Walden Y. Li
    The Ohio State University
  • Molly R. McKinney
    The Ohio State University
  • Jessica L. Irons
    The Ohio State University
  • Andrew B. Leber
    The Ohio State University
  • Footnotes
    Acknowledgements  This work was supported by BCS-1632296 and BCS-2021038 to A.B.L.
Journal of Vision September 2021, Vol.21, 2917. doi:
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      Walden Y. Li, Molly R. McKinney, Jessica L. Irons, Andrew B. Leber; Generalization of attentional control strategies across distinct tasks. Journal of Vision 2021;21(9):2917. doi:

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      © ARVO (1962-2015); The Authors (2016-present)

  • Supplements

When navigating in a grocery store, how do you quickly find an item on the shelves? Depending on your strategy choice, you can selectively search for items with a particular feature like color or shape, focus your attention to spatial locations where you predict the item might be, or just serially search through everything until you find the target. Recent research has shown that individuals vary substantially in strategies like these when approaching visual search tasks, but such strategies have not been shown to generalize across different visual search tasks (Clarke et al., 2020). We have hypothesized that strategy may generalize to some degree, specifically across tasks that make use of similar attentional components. This has led us to begin systematically probing which task components are necessary for generalization. Our approach is to have participants perform two tasks, in which some task component differs between the two, and measure whether strategy generalizes across the change. Here, we employ the Adaptive Choice Visual Search (ACVS; Irons & Leber, 2018), a paradigm explicitly designed to measure attentional control strategy. In two experiments, we had participants complete the standard ACVS and a modified task with one altered attentional component (specifically, the requirement to use feature-based attention and enumeration, respectively). The results showed positive correlations in strategy optimality between tasks that do or do not involve feature-based attention (r = .38, p = .0068) and across tasks that do or do not require enumeration (r = .33, p = .018). The results show that strategy can generalize across at least some changes in attentional task requirements. Future studies will continue to vary additional task components to determine the critical boundaries in which strategy generalization breaks down.


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