Age-Related Changes in Default Mode Network in Autism Spectrum Disorder: Insights From Effective Connectivity.

Researchers studied brain scans from over 1,300 people with and without autism across different ages. They found that brain connections in autism change as people get older. Young children with autism had more active brain connections, while teenagers and adults showed more mixed patterns with some connections being less active. Some brain connection patterns were linked to autism symptom severity, suggesting these could help doctors better understand and monitor autism.

This neuroimaging study analyzed brain connectivity patterns in the default mode network (DMN) across 1,316 participants with autism spectrum disorder (ASD) and typically developing controls from the ABIDE databases. Using advanced brain imaging techniques, researchers examined how connections within key brain regions change across childhood, adolescence, and adulthood. The study found distinct age-related patterns: children with ASD showed predominantly increased connectivity, while adolescents and adults displayed mixed patterns with more decreased connectivity. Importantly, age-by-group interactions were observed in children and adolescents but not adults, suggesting nonlinear developmental trajectories.

Several brain connections correlated with autism symptom severity, particularly in children and adults, indicating potential neural markers for diagnostic and monitoring purposes.

Findings suggest brain connectivity patterns could serve as biomarkers for autism diagnosis and monitoring. Age-specific differences highlight need for developmental considerations in assessment and intervention planning. Early hyper-connectivity transitioning to hypo-connectivity may inform timing of therapeutic interventions.

Study relies on cross-sectional rather than longitudinal data, limiting conclusions about individual developmental changes. Requires validation with larger datasets. Clinical utility of connectivity measures as biomarkers needs further investigation.

Altered brain connectivity in the default mode network (DMN) has frequently been reported in Autism Spectrum Disorder (ASD) patients compared to typically developing control (TC) participants. Most of these studies have focused on a specific age group or mixed-age groups with ASD. This study investigates age-related changes in effective connectivity (EC) within the DMN in individuals with ASD compared to TC. Using resting-state functional magnetic resonance imaging (MRI) data from the ABIDE-I and ABIDE-II databases, we analyzed 591 ASD and 725 TC participants across three age cohorts: children (≤ 12 years), adolescents (12-18 years), and adults (≥ 18 years).

Spectral Dynamic Causal Modeling was employed to estimate EC within the DMN, focusing on eight regions of interest: posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), left/right inferior parietal cortex (lIPC/rIPC), left/right middle temporal cortex (lMTC/rMTC), and left/right hippocampus (lHIP/rHIP). Parametric Empirical Bayes (PEB) analysis was used to assess group differences and age-related changes in EC, while controlling for covariates such as gender, handedness, eye status, and head motion. Key findings revealed significant group differences in EC between ASD and TC across all age groups. In children, ASD exhibited both hyper- and hypo-connectivity in various DMN connections, with most connections showing increased EC in ASD.

Adolescents and adults with ASD displayed a mixed pattern of group differences in EC, though the majority of connections showed hypo-connectivity in ASD. Age-by-group interactions observed in children and adolescents not adults, highlighted nonlinear developmental trajectories, with significant differences in EC patterns between ASD and TC. Additionally, in children and adults several extrinsic and intrinsic connections were associated significantly with diagnostic observation schedule (ADOS) symptom severity, such as overall ASD symptoms, communication and stereotyped behaviors, which these connections may serve as a neural marker of symptom severity in ASD. These findings underscore the dynamic nature of EC abnormalities in ASD across the lifespan, suggesting that early hyper-connectivity may transition to hypo-connectivity in later developmental stages.

The study highlights the potential of EC as a biomarker for ASD and emphasizes the importance of age-specific approaches in understanding the neural underpinnings of the disorder. Future research with larger datasets is needed to validate these findings and further explore the clinical relevance of EC in ASD diagnostics and interventions.