Matthias Kirschner is a clinician-scientist in the Department of Psychiatry at the UNIGE. He leads the Biomarker Unit at HUG and is Clinical Lead for Psychiatry at the HUG Outpatient Clinic for Mental and Brain Health at Campus Biotech. His laboratory uses multimodal neuroimaging and computational approaches to study brain network organization across psychosis, affective, and addictive disorders. His research integrates clinical, neuroimaging, and biological data to understand how neural, metabolic, and immune processes interact with cognitive–motivational function to shape vulnerability to mental illness.

At the interface between precision psychiatry and computational neuroscience, Matthias Kirschner aims to identify mechanistic biomarkers to predict clinical trajectories and guide personalised interventions. He is driven by a central question: why do some individuals develop mental disorders while others remain resilient? And how can this knowledge be translated into better strategies for prevention and treatment?

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Network and Clinical Neuroscience in Psychiatry

Matthias Kirchner and his team use large-scale neuroimaging, genetic, and clinical datasets to map how brain network and circuit organization varies across individuals with psychotic, affective, and addictive disorders — spanning the continuum from subclinical risk states in the general population to clinical disorder. Integrating network modeling and computational approaches, they aim to explain vulnerability, resilience, and disease progression across diagnoses and across the lifespan. Their overarching goal is to identify system-level markers of risk and clinical trajectories that can inform early intervention and personalized care.

Multimodal Deep Phenotyping and Clinical Translation

Matthias Kirchner and his team focus on motivational and cognitive dysfunction as transdiagnostic targets — symptoms that cut across diagnoses and remain among the hardest to treat. They approach these not as isolated brain deficits but as multidimensional, brain-body problems shaped by interacting neural, metabolic, and immune processes. Current work investigates how inflammation, oxidative stress, and excitation-inhibition imbalances alter brain networks and behavior, linking blood-based markers to brain signatures across diagnostic groups. Their goal is to develop individualized markers that support patient stratification, treatment targeting, and monitoring. Together, these insights translate into integrative strategies for personalized prevention and care — combining neuromodulation, targeted pharmacology, metabolic and anti-inflammatory approaches, and modular psychotherapy.