Mental health researchers face the conceptual challenge of developing new frameworks to understand and classify mental disorders and translating this knowledge into effective treatments. Current diagnostic classification systems [1–2] are effective in ensuring communication of diagnoses among clinicians but are largely “etiologically agnostic” when determining the biological nature of psychopathology [3]. High levels of psychiatric comorbidity and heterogeneity, fluid symptom trajectories, cross-diagnostic overlap in genetic and neurobiological factors, and the limited efficacy of many psychiatric treatments restrict our understanding of the neurobiology of mental illness based on categorical diagnoses [3–6]. An alternative approach is to exploit the new knowledge gained from advances in neuroimaging concerning the brain circuits involved in psychiatric symptoms to build a neurocircuit-based taxonomy for understanding and treating mental disorders. Indeed, clusters of individuals with neural network alterations have been identified in depression [7–8], psychotic disorders [9] and attention-deficit/hyperactivity disorder (ADHD [10]). Distinct neurocircuit alterations could help explain the heterogeneity of mental disorders, and targeted interventions focused on specific circuit dysfunctions could improve treatment efficacy and guide clinical practice.
