Patterns of connectome variability in autism across five functional activation tasks: findings from the LEAP project.

This study looked at brain scans of 282 autistic people and 221 non-autistic people while they did different thinking tasks. The research found that autistic brains connect differently during these tasks, especially in areas responsible for attention and social thinking. While each autistic person's brain worked differently from typical brains, there were similar patterns across all the different tasks they tried.

This large-scale neuroimaging study examined brain connectivity patterns in 282 autistic individuals and 221 typically developing controls aged 6-30 years using five different cognitive tasks. Researchers employed novel analytical methods including 'task potency' and normative modeling to identify how autistic brains engage differently with various cognitive challenges. Results showed that autistic individuals demonstrated globally atypical functional connectivity patterns across all tasks, with deviations primarily originating from prefrontal cortex and default mode network regions. Importantly, while connectivity patterns were atypical, they showed consistent spatial patterns across different tasks, suggesting systematic rather than random differences in brain network organization during cognitive processing.

Findings support individualized assessment approaches using neuroimaging markers. May inform development of targeted interventions focusing on prefrontal and default mode network function. Could guide personalized treatment planning by identifying specific brain network atypicalities in individual autistic people.

Study methodology details are limited in the abstract. Cross-sectional design cannot establish causality. Individual variability within autism group requires further investigation. Generalizability across different autism presentations and cognitive abilities unclear.

Autism spectrum disorder (autism) is a complex neurodevelopmental condition with pronounced behavioral, cognitive, and neural heterogeneities across individuals. Here, our goal was to characterize heterogeneity in autism by identifying patterns of neural diversity as reflected in BOLD fMRI in the way individuals with autism engage with a varied array of cognitive tasks. All analyses were based on the EU-AIMS/AIMS-2-TRIALS multisite Longitudinal European Autism Project (LEAP) with participants with autism (n = 282) and typically developing (TD) controls (n = 221) between 6 and 30 years of age. We employed a novel task potency approach which combines the unique aspects of both resting state fMRI and task-fMRI to quantify task-induced variations in the functional connectome.

Normative modelling was used to map atypicality of features on an individual basis with respect to their distribution in neurotypical control participants. We applied robust out-of-sample canonical correlation analysis (CCA) to relate connectome data to behavioral data. Deviation from the normative ranges of global functional connectivity was greater for individuals with autism compared to TD in each fMRI task paradigm (all tasks p < 0.001). The similarity across individuals of the deviation pattern was significantly increased in autistic relative to TD individuals (p < 0.002).

The CCA identified significant and robust brain-behavior covariation between functional connectivity atypicality and autism-related behavioral features. Individuals with autism engage with tasks in a globally atypical way, but the particular spatial pattern of this atypicality is nevertheless similar across tasks. Atypicalities in the tasks originate mostly from prefrontal cortex and default mode network regions, but also speech and auditory networks. We show how sophisticated modeling methods such as task potency and normative modeling can be used toward unravelling complex heterogeneous conditions like autism.