Age-related changes in brain signal variability in autism spectrum disorder.

backgroundBrain signal variability (BSV) is an important understudied aspect of brain function linked to cognitive flexibility and adaptive behavior. Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication difficulties and restricted and repetitive behaviors (RRBs). While atypical brain function has been identified in individuals with ASD using fMRI task-activation and functional connectivity approaches, little is known about age-related relationships with resting-state BSV and repetitive behaviors in ASD.

methodsWe conducted a cross-sectional examination of resting-state BSV and its relationship with age and RRBs in a cohort of individuals with Autism Brain Imaging Data Exchange (n = 351) and typically developing (TD) individuals (n = 402) aged 5-50 years obtained from the Autism Brain Imaging Data Exchange. RRBs were assessed using the Autism Diagnostic Interview-Revised (ADI-RRB) scale. BSV was quantified using the root-mean-square successive difference (rMSSD) of the resting-state fMRI time series. We examined categorical group differences in rMSSD between ASD and TD groups, controlling for both linear and quadratic age. To identify dimensional relationships between age, group, and rMSSD, we utilized interaction regressors for group x age and group x quadratic age. Within a subset of individuals with ASD (269 subjects), we explored the relationship between rMSSD and ADI-RRB scores, both with and without age considerations. The relationship between rMSSD and ADI-RRB scores was further analyzed while accounting for linear and quadratic age. Additionally, we investigated the relationship between BSV, age, and ADI-RRB scores using interaction regressors for age x RRB and quadratic age x RRB.

resultsWhen controlling for linear age effects, we observed significant group differences between individuals with ASD and TD individuals in the default-mode network (DMN) and visual network, with decreased BSV in ASD. Similarly, controlling for quadratic age effects revealed significant group differences in the DMN and visual network. In both cases, individuals with ASD showed decreased BSV compared with TD individuals in these brain regions. The group × age interaction demonstrated significant group differences in the DMN, and visual network brain areas, indicating that rMSSD was greater in older individuals compared with younger individuals in the ASD group, while rMSSD was greater in younger individuals compared with older individuals in the TD group. The group × quadratic age interaction showed significant differences in the brain regions included in DMN, with an inverted U-shaped rMSSD-age relationship in ASD (higher rMSSD in younger individuals that slightly increased into middle age before decreasing) and a U-shaped rMSSD-age relationship in TD (higher rMSSD in younger and older individuals compared with middle-aged individuals). When controlling for linear and quadratic age effects, we found a significant positive association between rMSSD and ADI-RRB scores in brain regions within the DMN, salience, and visual network. While no significant results were observed for the linear age × RRB interaction, a significant association between quadratic age and ADI-RRB scores emerged in the DMN, dorsal attention network, and sensorimotor network. Individuals with high ADI-RRB scores exhibited an inverted U-shaped relationship between rMSSD and age, with lower rMSSD levels observed in both younger and older individuals, and higher rMSSD in middle-aged individuals. Those with mid-range ADI-RRB scores displayed a weak inverted U-shaped rMSSD-age association. In contrast, individuals with low ADI-RRB scores showed a U-shaped rMSSD-age association, with higher rMSSD levels in younger and older individuals, but a lower rMSSD in middle-aged individuals.

conclusionThese findings highlight age-related atypical BSV patterns in ASD and their association with repetitive behaviors, contributing to the growing literature on understanding alterations in functional brain maturation in ASD.