December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Feature-temporal predictions can guide attention during visual search in dynamic scenes
Author Affiliations & Notes
  • Gwenllian C. Williams
    Department of Experimental Psychology, University of Oxford
  • Sage E. P. Boettcher
    Department of Experimental Psychology, University of Oxford
  • Nir Shalev
    Department of Experimental Psychology, University of Oxford
  • Anna C. Nobre
    Department of Experimental Psychology, University of Oxford
  • Footnotes
    Acknowledgements  NIHR Oxford Health Biomedical Research Centre; Wellcome Trust Senior Investigator Award to A.C.N. (104571/Z/14/Z); James S. McDonnell Foundation Understanding Human Cognition (number 220020448); The Wellcome Centre for Integrative Neuroimaging is supported by the Wellcome Trust (203139/Z/16/Z).
Journal of Vision December 2022, Vol.22, 3414. doi:https://doi.org/10.1167/jov.22.14.3414
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      Gwenllian C. Williams, Sage E. P. Boettcher, Nir Shalev, Anna C. Nobre; Feature-temporal predictions can guide attention during visual search in dynamic scenes. Journal of Vision 2022;22(14):3414. https://doi.org/10.1167/jov.22.14.3414.

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

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Abstract

Our world is dynamic, with various items coming in and out of view at different times. An efficient cognitive system should be able to allocate attention to relevant spatial locations, features, and moments in time. For example, when searching for a taxi you have ordered, you may hold expectations about the taxi’s colour, likely location, and time of arrival. Recent work using a novel dynamic visual search task has shown that spatiotemporal regularities can be used to guide attention towards targets in space and time. However, it remains unclear if feature-temporal regularities can also be used to improve our visual search performance. That is, when we hold no spatial expectations (i.e., we cannot predict the direction the taxi will arrive from), can we guide our attention based on featural and temporal expectations? We investigated this using an online dynamic visual search task that required participants to find and click on multiple targets in a search display. Targets and distractors faded in and out of view at different times during trials. The task contained feature-temporal regularities in that half of the targets in each trial always appeared in the same colour and at the same time. The remaining half of the targets appeared in an unpredictable colour and at an unpredictable time during trials, making them feature-temporally unpredictable. Participants located targets significantly more often, and significantly faster when they were feature-temporally predictable compared to when they were feature-temporally unpredictable. From this finding, we concluded that participants were able to use the feature-temporal regularities in the dynamic visual search task as a basis for attentional guidance. Further, no participants reported noticing feature-temporal regularities during the task, suggesting this attentional guidance may be implicit.

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