A Review of the Default Mode Network in Autism Spectrum Disorders and Attention Deficit Hyperactivity Disorder

Abstract

Functional magnetic resonance imaging (fMRI) has been widely used to examine the relationships between brain function and phenotypic features in neurodevelopmental disorders. Techniques such as resting-state functional connectivity (FC) have enabled the identification of the primary networks of the brain. One fMRI network, in particular, the default mode network (DMN), has been implicated in social-cognitive deficits in autism spectrum disorders (ASD) and attentional deficits in attention deficit hyperactivity disorder (ADHD). Given the significant clinical and genetic overlap between ASD and ADHD, surprisingly, no reviews have compared the clinical, developmental, and genetic correlates of DMN in ASD and ADHD and here we address this knowledge gap. We find that, compared with matched controls, ASD studies show a mixed pattern of both stronger and weaker FC in the DMN and ADHD studies mostly show stronger FC. Factors such as age, intelligence quotient, medication status, and heredity affect DMN FC in both ASD and ADHD. We also note that most DMN studies make ASD versus ADHD group comparisons and fail to consider ASD+ADHD comorbidity. We conclude, by identifying areas for improvement and by discussing the importance of using transdiagnostic approaches such as the Research Domain Criteria (RDoC) to fully account for the phenotypic and genotypic heterogeneity and overlap of ASD and ADHD. Impact statement In this work, we review the default mode network in autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD), as well as comorbid ASD+ADHD literature. Such a review has not been constructed in the field of cognitive neuroscience at this time, and it would greatly aid other behavioral and cognitive neuroscientists in identifying gaps in the field. In addition, the need to consider disorders to be on a continuum, as suggested by the Research Domain Criteria (RDoC), is important while identifying abnormal patterns in resting-state functional connectivity. This timely review will impact the field in a meaningful way, such that more research on the overlaps between ASD and ADHD is conducted along a spectrum.