Investigating functional brain network integrity using a traditional and novel diagnostic system for neurodevelopmental disorders
BackgroundCurrent diagnostic systems for neurodevelopmental disorders do not have clear links to underlying neurobiology, limiting their utility in identifying targeted treatments for individuals. Several factors contribute to this issue, including the use of small samples in neuroimaging research and heterogeneity within diagnostic categories. Here, we aimed to investigate differences in functional brain network integrity between traditional diagnostic categories (autism spectrum disorder [ASD], attention-deficit/hyperactivity disorder [ADHD], typically developing [TD]) and carefully consider the impact of comorbid ASD and ADHD on functional brain network integrity in a large sample. We also assess the neurobiological validity of a novel, potential alternative nosology based on behavioral measures of executive function.\n\nMethodFive-minute resting-state fMRI data were obtained from 168 children (128 boys, 40 girls) with ASD, ADHD, comorbid ASD and ADHD, and TD children. Independent component analysis and dual regression were used to compute within- and between-network functional connectivity metrics at the individual level.\n\nResultsNo significant group differences in within- nor between-network functional connectivity were observed between traditional diagnostic categories (ASD, ADHD, TD) even when stratified by comorbidity (ASD+ADHD, ASD, ADHD, TD). Similarly, subgroups classified by executive functioning levels showed no group differences.\n\nConclusionsUsing clinical diagnosis and behavioral measures of executive function, no group differences were observed among the categories examined. Therefore, we suggest that brain imaging metrics may more effectively define clinical subgroups than behavioral metrics, and may contribute to the establishment of a neurobiologically valid nosology for neurodevelopmental disorders.