From recognition to regulation: Combining meta-analytic priors with machine learning for decoding affective brain–behavior relationships in health and disease

• Applicants: Dr. Robert Langner; Dr. Veronika Müller
• Subject Area: Biological Psychiatry
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 552339449

Human emotion processing is a broad concept that encompasses different aspects of affective processes and behavior like emotion perception, explicit identification, experience, regulation and expression. While these subdomains of emotion processing are assumed to be subserved by common (emotion-general) as well as different (aspect-specific) brain regions, comprehensive systematic comparisons are lacking. Besides individual differences in the normal spectrum, severe changes of emotional functioning and impairments of emotion processing are observed in various psychiatric diseases including schizophrenia and depression. However, given the heterogeneity of results in patients, these diseases might not be associated with a generalized dysfunction in emotion-related brain networks but rather with dysfunctions that are specific to different aspects of emotion processing. The main objective of the planned project is to delineate those brain networks that are robustly and specifically associated with the different subdomains of emotion processing and to test how functional connectivity patterns of the resulting networks predict different aspects of individual emotion processing in healthy adults as well as to classify patients with schizophrenia or depression and predict their symptom severity. To this end, we will first identify brain networks subserving the fundamental aspects of emotion processing by means of coordinate-based meta-analyses. In a second step, the networks identified will be used as spatial priors for investigating affective brain–behavior relationships in healthy adults and clinical populations using machine learning.

• DFG Programme: Research Grants
• International Connection: USA
• Cooperation Partner: Professor Dr. Vaibhav Diwadkar