ArticlePsychonomic bulletin & review2025
Information sampling differences supporting superior face identity processing ability.
Article in Psychonomic bulletin & review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Super-recognizers sample visual information of superior computational value for facial recognition.Proceedings. Biological sciences · 2025Article
- Normative face recognition ability test scores vary across online participant pools.Scientific reports · 2025Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Face recognition in humans is often cited as a model example of perceptual expertise that is characterized by an increased tendency to process faces as holistic percepts. However emerging evidence across different domains of expertise points to a critical role of feature-based processing strategies during the initial encoding of information. Here, we examined the eye-movement patterns of super-recognisers-individuals with extremely high face identification ability compared with the average person-using gaze-contingent "spotlight" apertures that restrict visual face information in real time around their point of fixation. As an additional contrast, we also compared their performance with that of facial examiners-highly trained individuals whose superiority has been shown to rely heavily on featural processing. Super-recognisers and facial examiners showed equivalent face matching accuracy in both spotlight aperture and natural viewing conditions, suggesting that they were equally adept at using featural information for face identity processing. Further, both groups sampled more information across the face than controls. Together, these results show that the active exploration of facial features is an important determinant of face recognition ability that generalizes across different types of experts.
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