Despite extensive research into the neural basis of autism spectrum disorder (ASD), the presence of substantial biological and clinical heterogeneity among diagnosed individuals remains a major barrier. Commonly used case‒control designs assume homogeneity among subjects, which limits their ability to identify biological heterogeneity, while normative modeling pinpoints deviations from typical functional network development at individual level.

Using a world-wide multi-site database known as Autism Brain Imaging Data Exchange, we analyzed individuals with ASD and typically developed (TD) controls (total n = 1218) aged 5–40 years, generating individualized whole-brain network functional connectivity (FC) maps of age-related atypicality in ASD. We then used local polynomial regression to estimate a networkwise normative model of development and explored correlations between ASD symptoms and brain networks.

We identified a subset exhibiting highly atypical individual-level FC, exceeding 2 standard deviation from the normative value. We also identified clinically relevant networks (mainly default mode network) at cohort level, since the outlier rates decreased with age in TD participants, but increased in those with autism. Moreover, deviations were linked to severity of repetitive behaviors and social communication symptoms.

Individuals with ASD exhibit distinct, highly individualized trajectories of brain functional network development. In addition, distinct developmental trajectories were observed among ASD and TD individuals, suggesting that it may be challenging to identify true differences in network characteristics by comparing young children with ASD to their TD peers. This study enhances understanding of the biological heterogeneity of the disorder and can inform precision medicine.