Mental Health Mapping
We use large, diverse datasets and machine learning to understand how biological, social, and environmental factors shape individual mental health, and we work with patients and clinicians to translate these insights into clinical care.
Foundations
What is healthy, and what is a disorder?
Structures
From biology to families and society.
Markers
The hidden factors behind illness.
Models
Machine learning, from lab to clinic.
Recent Highlights
Paper · Oct 2026
npj Digital Medicine
Accepted: Alexander Frotscher's large-scale benchmark of anomaly detection in brain imaging.
Talk & paper · Oct 2026
MICCAI 2026 (Main Track)
Mariam Zabihi presented SIGMA-VAE, our multi-view autoencoder for normative modeling, with a talk and a paper in the main track.
Workshop · Oct 2026
We helped organize the Machine Learning in Clinical Neuroimaging (MLCN) workshop at MICCAI for the eighth time.
Lab life · Oct 2026
We had a wonderful lab retreat with friends in Jena.
Conference · Oct 2026
As a member of the Scientific Program Committee, Thomas Wolfers enjoyed a wonderful ECNP Congress 2026 in Munich with 6,000 attendees.
Paper · Aug 2026
Nature Neuroscience
Accepted: Yanwu Yang's normative reference for human brain dynamics across the lifespan.
Talk & preprint · Jun 2026
Nitin Sharma presented transferable conditional brain charts, which link brain structure to Alzheimer's disease progression, at OHBM 2026; the preprint is now on arXiv.
Led by Thomas Wolfers at Friedrich Schiller University Jena.