Klaus Mathiak

Probe the self-regulation of CS networks in adults and adolescents diagnosed with mental disorders related to frequent stress-associated affective outbursts and aggressive symptoms in posttraumatic stress disorder (PTSD), and BPD. The patients will subsequently be trained to regulate the frontal control network to varying acute threat in a double-blind, randomized, controlled design. An immersive, virtual brain- computer-interface (BCI) will allow for a culture- and age-sensitive, personalized training approach. The aim of the present investigation is to assess feasibility of the approach according to four clinical markers: Reduction of perceived threat and aggressive behavior in daily life, improved control in the face of unfair provocation, and neurofeedback-specific modulation of the neural networks.

Develop virtual scenarios to assess decision strategies in cartoon-like and naturalistic contexts. The core question is how healthy individuals and patients make (mal-)adaptive aggressive decisions in social conflicts given their threat sensitivity, cognitive functions, and learning experience. We plan to present mathematically well-defined aggressive decision scenarios to healthy participants as well as patients across diagnostic categories with high scores of aggressive behavior, threat sensitivity, and inference of hostile intent in others. Computational models that accurately explain behavioral choices and neural responses (tested using fMRI and pupillometry) will be developed to identify the aggressive decision strategies humans employ in approach-avoidance conflicts of increasing complexity and ecological realism. The purpose will be to determine if patients use overly aggressive strategies that are not warranted by the necessary defense of self-threats and underlying neural circuits.

Data management and training platform. A decentralized data management infrastructure will help focus on developmental and therapeutic longitudinal data, training all participating researchers in the necessary skills for future use. This strategy will lay the foundations for further data-driven computational modelling projects in the next funding period.