Borgwardt

Department of Psychiatry and Psychotherapy

Group Members

Stefan Borgwardt (Group leader)
TBA


Research Interests

Our group investigates the complex interplay of biological, cognitive and psychological factors leading to the emergence of psychiatric disorders, with a special focus on psychotic and affective disorders. Our work is informed by multiple clinical and scientific disciplines, and uses a variety of methods including structural and functional magnetic resonance imaging (MRI), electroencephalography (EEG), machine learning, computational modeling, pharmacological challenge, and imaging genetics.

In current research projects, we investigate neural mechanisms leading to the emergence of psychiatric disorders, with a particular focus on

  • establishing robust biomarkers for prediction of clinical outcomes in young people at high risk and in patients with an established psychiatric disorder
  • the efficacy and action mechanisms of established and novel treatments for psychotic disorders, including pharmacological agents, psychotherapeutic approaches and therapeutic videogames.
  • the effects of gut microbiota on brain structure and mental health, and the relevance of interventions targeting the gut microbiota for the treatment of major depressive disorder
  • the effects of hallucinogens on brain function and the potential utility of LSD for treatment of anxiety and depression.


Collaborations

  • King’s College London
  • University of Oslo, Norway
  • Flinders University, South Australia
  • Institute of Nanoscience and Nanotechnology, National Center for Scientific Research "Demokritos", Athens, Greece
  • University of Basel, Switzerland
  • ETH Zürich, Switzerland


Publications

  1. Andreou C, Borgwardt S. Structural and functional imaging markers for susceptibility to psychosis. Molecular Psychiatry, in press.
  2. Diaconescu, A.O., Hauke, D.J. & Borgwardt, S. Models of persecutory delusions: a mechanistic insight into the early stages of psychosis. Mol Psychiatry 24, 1258–1267 (2019).
  3. Koutsouleris N, Kambeitz-Ilankovic L, Ruhrmann S, et al. Prediction Models of Functional Outcomes for Individuals in the Clinical High-Risk State for Psychosis or With Recent-Onset Depression: A Multimodal, Multisite Machine Learning Analysis. JAMA Psychiatry. 2018;75(11):1156–1172.
  4. Moritz S, Mahlke C, Westermann S, Ruppelt F, Lysaker PH, Bock T, Andreou C. Embracing psychosis: A cognitive insight intervention improves personal narratives and meaning-making in patients with schizophrenia. Schizophr Bull 2018;44:307-316.
  5. Andreou C, Steinmann S, Kolbeck K, Rauh J, Leicht G, Moritz S, Mulert C. The role of effective connectivity between the task-positive and task-negative network for evidence gathering. Neuroimage. 2018;173:49-56.