期刊
DEVELOPMENTAL COGNITIVE NEUROSCIENCE
卷 42, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.dcn.2020.100754
关键词
Autism Spectrum Disorder; Individual differences; Numerical problem-solving; Decision-making; Brain imaging
资金
- NIH [MH084164, HD059205, MH121069]
- Stanford Child Health Research Institute
- Stanford NIH-National Center for Advancing Training Sciences-Clinical and Translational Science Awards program [TR001085]
- Agence Nationale de la Recherche [ANR-18-CE28-0010]
- Universite de Paris (IdEx)
Heterogeneity in cognitive and academic abilities is a prominent feature of autism spectrum disorder (ASD), yet little is known about its underlying causes. Here we combine functional brain imaging during numerical problem-solving with hierarchical drift-diffusion models of behavior and standardized measures of numerical abilities to investigate neural mechanisms underlying cognitive variability in children with ASD, and their IQ-matched Typically Developing (TD) peers. Although the two groups showed similar levels of brain activation, the relation to individual abilities differed markedly in ventral temporal-occipital, parietal and prefrontal regions important for numerical cognition: children with ASD showed a positive correlation between functional brain activation and numerical abilities, whereas TD children showed the opposite pattern. Despite similar accuracy and response times, decision thresholds were significantly higher in the ASD group, suggesting greater evidence required for problem-solving. Critically, the relationship between individual abilities and engagement of prefrontal control systems anchored in the anterior insula was differentially moderated by decision threshold in subgroups of children with ASD. Our findings uncover novel cognitive and neural sources of variability in academically-relevant cognitive skills in ASD and suggest that multilevel measures and latent decision-making dynamics can aid in characterization of cognitive variability and heterogeneity in neurodevelopmental disorders.
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