August 2016
Volume 16, Issue 12
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2016
Eye movement patterns during scene viewing predict individual differences
Author Affiliations
  • Taylor Hayes
    Center for Mind and Brain, University of California, Davis
  • John Henderson
    Center for Mind and Brain, University of California, Davis
Journal of Vision September 2016, Vol.16, 329. doi:
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      Taylor Hayes, John Henderson; Eye movement patterns during scene viewing predict individual differences. Journal of Vision 2016;16(12):329. doi:

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

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An important and understudied area in scene perception is the degree to which individual differences influence scene-viewing behavior. The present study investigated this issue by predicting individual differences from regularities in sequential eye movement patterns. Seventy-nine participants completed a free-view memorization task for 40 real-world scenes while their eye movements were recorded. Individual difference measures were collected across subsets of participants including cognitive ability measures (e.g., working memory capacity) and cognitive disorder measures (e.g., autism spectrum disorder: ASD). An area of interest grid composed of 5 radiating rectangular areas from the scene center to the periphery was used to represent observers' tendencies to shift their attention between more central or peripheral scene information. Successor Representation Scanpath Analysis (SRSA, Hayes, Petrov, & Sederberg, 2011) was used to capture statistical regularities in each participant's eye movements across this predefined area of interest grid. A principal component analysis of participant successor representations was performed for each individual difference measure, and these components were then used to predict individual differences scores. SRSA was able to predict several individual difference measures well. Leave-one-out cross validation demonstrated significant prediction across the following measures: working memory capacity (r2=0.45), fluid intelligence (r2=0.43), SAT (r2=0.45), and ASD (r2=0.26). Moreover, the component regression weights were readily interpretable in terms of broad scanning strategies. For instance, higher cognitive ability was associated with the tendency to focus attention more centrally within a scene, and move more systematically among these central areas. Participants with higher ASD scores showed a different pattern, with a greater tendency to focus attention more peripherally within a scene, and move less systematically between the center and periphery of the scene. These results suggest that underlying individual differences in observers significantly influence gaze behavior during real-world scene perception.

Meeting abstract presented at VSS 2016


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