Mental disorders are among the most common and most serious health problems. Across the population, one in three people are affected at some point in their lives. The chances of successful treatment improve with early, precise and individualized treatment. Therefore, researchers from Justus-Liebig-University Gießen, Goethe-University Frankfurt and Technical University of Darmstadt, under the leadership of Philipps-University Marburg, want to jointly develop new therapeutic approaches and methodologies.

At DYNAMIC, scientists from psychology, psychiatry, statistics, and computer science work together with a shared vision of better understanding mental disorders. To do this, we utilize multimodal, dynamic data for the individual characterization of mental disorders. Specifically, we utilize dynamic networks and machine learning models and also work to further develop these research methods.

The aim of the project is to advance the diagnosis of mental disorders, patient care and the development of methods. Our goal is to move away from describing mental disorders as simplified, separate categories and towards a description that embraces the heterogeneity of individual problems and formalizes them accordingly. Fundamental to this is an understanding of mental health problems as disorders of dynamic networks of psychopathological, psychological and neurobiological processes.