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Updated: Jan 23, 2026

Immunohistochemical Visualization of Hippocampal Neuron Activity After Spatial Learning in a Mouse Model of Neurodevelopmental Disorders
Published on: May 12, 2015
The spectrum of neurodevelopmental disorders: comorbidities as clues to pathogenesis
Catherine M McHugh1,2, James R John1,2,3, Weng Tong Wu1
1Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, Sydney.
Purpose Of Review:
High comorbidity rates across neurodevelopmental disorders (NDDs) may suggest shared pathogenic mechanisms rather than independent disease processes. This review synthesizes recent neuroimaging evidence (2024-2025) examining how comorbidity patterns reveal circuit-level convergence across traditional diagnostic boundaries.
Recent Findings:
Studies of brain connectivity demonstrate that four core transdiagnostic dimensions of cognitive rigidity, sensory processing, repetitive behaviours, and social-emotional regulation show both circuit convergence and disorder-specific patterns across autism spectrum disorder, attention deficit hyperactivity disorder, obsessive compulsive disorder, Tourette syndrome and anxiety disorders. Analyses of how brain networks change over time clarify inconsistencies in earlier static studies, revealing that temporal network inflexibility predicts symptom severity better than anatomical connectivity alone. Developmental studies suggest circuit dysfunction emerges early (as early as 18 months for sensory processing) and creates cascade effects throughout maturation. Interventions targeting specific brain circuits produce transdiagnostic improvements, validating circuit-based approaches over disorder-specific supports.
Summary:
Comorbidity patterns provide critical clues to shared pathogenesis, with circuit-level evidence supporting dimensional models over categorical diagnoses. The timing and of circuit dysfunction inform whether patterns reflect shared vulnerabilities, developmental cascades, or independent processes converging on similar phenotypes. These findings suggest that assessments and interventions targeting underlying brain mechanisms may be more effective than traditional categorical diagnosis-based interventions.
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