Neuroimaging Biomarkers for ADHD and ASD: Recent Advances, Transdiagnostic Overlaps, and Implications for Precision Psychiatry

Neurodevelopmental disorders such as Attention-Deficit/Hyperactivity Disorder (ADHD) and autism spectrum disorder (ASD) are highly prevalent, often comorbid conditions that significantly impact cognitive, behavioural, and social functioning. Neuroimaging has emerged as an important tool in understanding the underlying neural mechanisms of these disorders, contributing to efforts toward biologically grounded diagnosis and personalised intervention. This review synthesises findings from 28 recent neuroimaging studies (20222025) using MRI, fMRI, EEG, and advanced computational modelling to examine structural, functional, and network-level abnormalities in ADHD and ASD, as well as transdiagnostic overlaps. ADHD-specific studies highlight fronto-striatal dysconnectivity, delayed cortical maturation, and reduced basal ganglia iron levels, with recent advances in machine learning enhancing precision phenotyping. ASD-focused research underscores heterogeneity in cerebellar morphology, atypical predictive coding, and genetically driven cortical thinning. Transdiagnostic investigations reveal converging alterations in executive control networks and shared dimensional traits across diagnostic boundaries, supporting dimensional models of neurodevelopment. Despite these advances, challenges remain, including small and heterogeneous samples, overreliance on cross-sectional data, limited reproducibility, and interpretability issues in multimodal integration. The review concludes by advocating for longitudinal, harmonised, and multisite neuroimaging designs aligned with frameworks like the Research Domain Criteria (RDoC), as well as the incorporation of machine learning models that integrate cognitive, clinical, and biological data. By identifying shared and distinct neural markers, this review aims to support the development of robust, developmentally informed, and transdiagnostically valid neuroimaging biomarkers to inform early diagnosis and tailored interventions in neurodevelopmental disorders.