Subdomains of executive function correlate with accuracy on a change detection task.

Norman A; Conduit R; Laycock R; Robinson, SR · 2026 · PubMed Central

DOI: 10.3758/s13423-026-02937-0

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Summary

This study investigates the cognitive subdomains that contribute to individual differences in change detection accuracy, addressing a gap in literature where previous tasks often lacked sufficient variance to correlate with cognitive measures. Change blindness—the failure to detect visual changes despite their availability to perception—is critical for behaviors like driving and radiology. While attention and working memory are known to be involved, the specific interplay of executive function subdomains remains unclear. The authors hypothesized that performance on a battery of executive function and processing speed tests would significantly correlate with change detection accuracy. The researchers utilized a naturalistic change detection task, the Alternate Forms Flicker Task (AFFT), which avoids ceiling effects by producing a wide spread of accuracy scores. This was paired with a battery of nine cognitive tests assessing attention, visuospatial working memory, cognitive flexibility, and processing speed. The sample consisted of 260 participants aged 18–57, recruited from a larger study pool. The AFFT involved identifying missing targets in flickering images, with a 30-second time limit per trial. The cognitive battery included tasks such as the Flanker Arrow Task, Multiple Object Tracking, Austin Maze, Object 2back Task, Wisconsin Card Sorting Test, and the Subtle Cognitive Impairment Test. Data were analyzed using exploratory factor analysis to identify latent cognitive structures, followed by multiple linear regression to determine which factors predicted AFFT accuracy. Factor analysis extracted three distinct factors: Cognitive Flexibility, Visuospatial Working Memory, and Attention and Processing Speed, which collectively accounted for 41% of the variability in the test battery scores. Strongest individual correlates with AFFT accuracy were tasks measuring top-down attentional search, visuospatial ability, and visual inspection time. The multiple linear regression model using these three factors significantly accounted for 10.0% of the variability in AFFT scores. Visuospatial working memory emerged as the principal predictive factor, indicating that individual differences in this domain are the primary driver of differences in change detection accuracy. The findings suggest that successful change detection relies heavily on visuospatial working memory, alongside contributions from attentional control and processing speed. By using a task with adequate discriminatory power, the study clarifies that change blindness is not solely an attentional failure but involves specific memory encoding and comparison processes. These results have implications for understanding individual differences in visual perception and may inform training or assessment protocols in professions requiring high vigilance and change detection, such as aviation and medical imaging.

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Topics

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• cognitive capacity variation
• inattentional change blindness