December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Attention to social interactions in real-world scenes: evidence from change blindness
Author Affiliations
  • Mahsa Mirza Hossein Barzy
    University of Reading
  • Rachel Morgan
    University of Reading
  • Richard Cook
    Birkbeck, University of London
  • Katie L.H. Gray
    University of Reading
Journal of Vision December 2022, Vol.22, 3600. doi:https://doi.org/10.1167/jov.22.14.3600
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      Mahsa Mirza Hossein Barzy, Rachel Morgan, Richard Cook, Katie L.H. Gray; Attention to social interactions in real-world scenes: evidence from change blindness. Journal of Vision 2022;22(14):3600. https://doi.org/10.1167/jov.22.14.3600.

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

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Abstract

In flicker paradigms, changes to social or animate aspects of a scene are better detected compared to non-social or inanimate aspects. Whilst previous studies have focused on how changes to individual faces/bodies are detected, it is possible that individuals presented within a social interaction may be further prioritised, as the accurate interpretation of social interactions may convey an evolutionary advantage. Over three experiments, we explored change detection to complex real-world scenes containing multiple individuals and objects. We manipulated scenes so that changes either occurred by the removal of a) an individual who was not in a social interaction, b) an individual who was in a social interaction, or c) an object. In Experiment 1 (N = 50), we measured change detection for non-interacting individuals versus objects. In Experiment 2 (N = 49), we measured change detection for interacting individuals versus objects. Finally, in Experiment 3 (N = 85), we measured change detection for non-interacting versus interacting individuals. To determine whether any differences were not driven by low-level visual features, we also ran an inverted version of each task. In Experiments 1 and 2, we found that changes to non-interacting and interacting individuals were detected more quickly than changes to objects. We found inversion effects for both non-interaction and interaction changes, whereby they were detected more quickly when upright compared to inverted. No inversion effect was seen for objects. This suggests that the high-level, social content of the images was driving the improved change detection versus objects. When directly comparing changes for individuals in non-interactions versus interactions, we found that non-interacting individuals were detected slightly faster than those interacting. Our results replicate the social advantage often found in change detection paradigms. However, individuals presented within social interaction configurations do not appear to be more easily detected than those in non-interacting configurations.

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