Cross-sectional studies reported inconsistent findings on distinctive neuroanatomical characteristics of Autism Spectrum Disorders (ASD). We set up a lifespan study through a series of machine-learning-based case-control comparisons made on sub-cohorts obtained by partitioning a large structural MRI data sample (age range: 2-25 years) in subsamples with partially-overlapping narrower age ranges (3-4 years). We implemented One-Class Support Vector Machines on these sub-cohorts, obtaining the temporal evolution of the case-control separation ability, which is related to the detectability of neuroimaging-based biomarkers. Distinctive common features characterize children with ASD under 5 years of age; the heterogeneity of the ASD condition dominates from adolescence.
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