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Clinically relevant autistic traits predict greater reliance on detail for image recognition.


ABSTRACT: Individuals with an autism spectrum disorder (ASD) diagnosis are often described as having an eye for detail. But it remains to be shown that a detail-focused processing bias is a ubiquitous property of vision in individuals with ASD. To address this question, we investigated whether a greater number of autistic traits in neurotypical subjects is associated with an increased reliance on image details during a natural image recognition task. To this end, we use a novel reverse correlation-based method (feature diagnosticity mapping) for measuring the relative importance of low-level image features for object recognition. The main finding of this study is that image recognition in participants with an above-median number of autistic traits benefited more from the presence of high-spatial frequency image features. Furthermore, we found that this reliance-on-detail effect was best predicted by the presence of the most clinically relevant autistic traits. Therefore, our findings suggest that a greater number of autistic traits in neurotypical individuals is associated with a more detail-oriented visual information processing strategy and that this effect might generalize to a clinical ASD population.

SUBMITTER: Alink A 

PROVIDER: S-EPMC7455566 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Clinically relevant autistic traits predict greater reliance on detail for image recognition.

Alink Arjen A   Charest Ian I  

Scientific reports 20200828 1


Individuals with an autism spectrum disorder (ASD) diagnosis are often described as having an eye for detail. But it remains to be shown that a detail-focused processing bias is a ubiquitous property of vision in individuals with ASD. To address this question, we investigated whether a greater number of autistic traits in neurotypical subjects is associated with an increased reliance on image details during a natural image recognition task. To this end, we use a novel reverse correlation-based m  ...[more]

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