PREACT

Dysfunctional emotion regulation has been identified as a hallmark feature of psychopathology across internalizing mental disorders and is often reflected by the overuse of maladaptive strategies. Cognitive-behavioral therapy (CBT) that uses techniques directly targeting e.g. reappraisal skills can improve emotion regulation abilities, and CBT treatment outcome has been associated with brain response during emotion regulation. It has been suggested that the functioning of the neural circuitry supporting emotion regulation capacities may be a “gateway” to receiving benefits from psychotherapy. Pretreatment brain response during emotion regulation may thus provide a valid transdiagnostic predictor for CBT outcome. Data from functional connectivity studies indicate that disrupted prefrontal-limbic connectivity may underlie deficits in emotion regulation interpreted in terms of an ineffective top-down control resulting in a failure to down-regulate negative emotions. The early identification of patients with suboptimal configuration in these circuits, being vulnerable to therapy non-response, could aid the tailoring of specific treatments or augmentation strategies in order to achieve optimized therapeutic results. The main objectives of SP8 are the development and validation of neuro-functional markers of emotion regulation as predictors of CBT non-response in a transdiagnostic sample of patients across the internalizing spectrum. We will develop effective connectivity models of fronto-limbic modulation during three different emotion regulation strategies in order to establish a set of models with the best predictive values for non-response to CBT treatment in retrospective data sets of patients with depressive, obsessive-compulsive, and social anxiety disorder. We will then validate our models in the transdiagnostic prospective sample of the proposed research unit cohort, also testing for generalization and specificity across tasks and diagnoses. We will refine our models by including behavioral markers of emotion regulation from clinical measures (SP5) and digital phenotyping (SP6), exchange results with SP4 to develop psychometric measurement models of emotion regulation using BOLD, electro-encephalographic and heart rate variability data, and compare task-based effective connectivity measures with resting-state connectivity (SP7). Finally, we will share our data with SP2 for single-case prediction.