Scan patterns during real-world scene viewing predict individual differences in cognitive capacity

Aug 25, 2026

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Scan patterns in real-world scene viewing vary across individuals, yet the link between these scan-pattern differences and cognitive differences remains insufficiently understood due to the difficulty of analyzing scan patterns. This study applies Successor Representation Scanpath Analysis to measure how scan-pattern variability relates to individual differences in intelligence, working memory capacity, and processing speed. Results show scan-pattern differences explain over 40% of variance in intelligence and working memory and more than one third of processing-speed variance. The findings inform gaze-control models and future individual-differences research.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages17

Reading Time43 min

AccessFree to download

Introduction

Background on scan patterns and gaze control

Individual differences and analysis challenges

Successor Representation Scanpath Analysis

Methods and Results

Quantifying associations with cognitive measures

Variance explained across cognitive domains

Discussion

Implications for gaze-control models

Future research directions

Scan patterns during real-world scene viewing predict individual differences in cognitive capacity Taylor R . Hayes Center for Mind and Brain, University of California, Davis, CA, USA \# $ Center for Mind and Brain and Department of John M . Henderson Psychology, University of California, Davis, CA, USA \# $ From the earliest recordings of eye movements during active scene viewing to the present day, researchers have commonly reported individual differences in eye movement scan patterns under constant stimulus and task demands. These findings suggest viewer individual differences may be important for understanding gaze control during scene viewing. However, the relationship between scan patterns and viewer individual differences during scene viewing remains poorly understood because scan patterns are difficult to analyze. The present study uses a powerful technique called Successor Representation Scanpath Analysis (Hayes, Petrov, & Sederberg, 2011, 2015) to quantify the strength of the association between individual differences in scan patterns during real-world scene viewing and individual differences in viewer intelligence, working memory capacity, and speed of processing. The results of this analysis revealed individual differences in scan patterns that explained more than 40% of the variance in viewer intelligence and working memory capacity measures, and more than a third of the variance in speed of processing measures. The theoretical implications of our findings for models of gaze control and avenues for future individual differences research are discussed. When viewing a scene, we actively move our eyes three to four times each second to sample the visual environment (Henderson, 2003) . The series of eye movements during scene viewing can broadly be categorized into periods where our eyes are held relatively stable (ﬁxations) and periods where our eyes rapidly move between two different spatial locations (saccades) . During ﬁxation periods, the area of the eye’s retina with the highest acuity is directed to aspeciﬁc location within the scene and high-quality visual information is acquired. In contrast, limited visual information is acquired during the rapid saccadic eye movements between ﬁxations—a phenomena known as saccadic suppression (Matin, 1974; Thiele, Henning, Kubischik, & Hoffman, 2002) . The result of viewing a real-world scene is a complex, sequential pattern of ﬁxations and saccades called ‘‘scanpaths’’ or‘‘scan patterns’’ (Noton & Stark, 1971a, 1971b; Stark & Ellis, 1981; see Figure 1) . Scan patterns provide a rich description of how overt visual attention is used to sequentially ﬁlter our visual environment in an effort to satisfy ongoing perceptual, cognitive, and behavioral goals (Churchland, Ramachandran, & Sejnowski, 1994; Findlay & Gilchrist, 2003), and have the potential to provide important insights into the underlying mechanisms of gaze control during scene viewing. Pioneering work on scene viewing by Buswell (1935) and Yarbus (1967) produced early qualitative ﬁndings that described differences in scan patterns related to the properties of the scene stimulus, the scene task, and the viewer. Since this early scene work, there has been a great deal of research investigating how image properties such as color, intensity, and orientation contribute to bottom-up scene saliency (Itti & Koch, 2000, 2001; Koch & Ullman, 1985; Torralba, 2003), and the ways in which visual saliency inﬂuences where people look in a given scene (Bruce & Tsotsos, 2009; Koehler, Guo, Zhang, & Eckstein, 2014; Parkhurst, Law, & Niebur, 2002) . More recently, there has been a renewed interest in attempting to quantify the extent to which eye movements reﬂect top-down cognitive relevance asa function of scene viewing task. For instance, it has been shown that scene task can be predicted at abovechance levels from ﬁxation number, ﬁxation duration, and saccade amplitude distributions (Borji & Itti, 2014; Hender

FAQs

What method does the study use to analyze scan patterns?

The study uses Successor Representation Scanpath Analysis to quantify associations between scan-pattern variability and individual cognitive differences.

Which cognitive capacities are predicted by scan patterns?

Scan patterns predict individual differences in viewer intelligence, working memory capacity, and speed of processing.

How much variance do scan-pattern differences explain?

Scan-pattern differences explain more than 40% of variance in intelligence and working memory measures, and more than a third of variance in processing-speed measures.

Aug 25, 2026

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