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Linking Subclinical Autistic Traits and Perceptual Category Learning
Claire V Warren1,2,3, Rebekka Baumert1, Kira Diermann1
1Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
The European Journal of Neuroscience
|February 17, 2025
Summary
Individuals with higher autistic traits showed poorer accuracy in perceptual categorization tasks. This was linked to altered neural activity in visual processing and decision-making, not a deficit in prototype abstraction.
Area of Science:
- Neuroscience
- Cognitive Psychology
- Psychiatry
Background:
- Autism spectrum condition (ASC) is a neurodevelopmental condition characterized by social interaction and communication difficulties, alongside repetitive behaviors.
- Individuals with ASC often face challenges in non-social cognitive processing, including visual categorization based on holistic appearance.
- Atypicalities in abstracting category prototypes or general visual category learning may underlie these difficulties, with milder traits seen in the broader autism phenotype.
Purpose of the Study:
- To investigate the relationship between autistic traits and visual category learning in neurotypical adults.
- To examine behavioral performance and neural correlates using event-related functional magnetic resonance imaging (fMRI).
- To explore whether autistic traits are associated with difficulties in prototype abstraction versus other visual category learning processes.
Main Methods:
- Compared neurotypical adults with high versus low autistic traits on a perceptual categorization task using a dot-pattern paradigm.
- Utilized event-related fMRI to measure neural activity during task performance.
- Employed Bayesian computational modeling to assess category knowledge representation (prototype vs. exemplars) and decision policies.
Main Results:
- Higher autistic traits correlated with reduced accuracy in endorsing category members.
- Significant differences in neural correlates were observed between groups during training, particularly in visual processing (occipital regions), decision-making (midfrontal regions, posterior cingulate), and feedback processing (posterior cingulate, ventral striatum).
- Computational modeling indicated stricter decision policies in individuals with higher autistic traits, but did not support a deficit in prototype abstraction.
Conclusions:
- Difficulties in visual category learning associated with autistic traits are not primarily due to problems with prototype abstraction.
- Atypicalities in visual processing, decision-making, and feedback processing contribute to altered category learning in individuals with higher autistic traits.
- These findings highlight broader visual category learning atypicalities rather than specific prototype deficits in the context of autistic traits.
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