Clinical Research Directory

Approach-Avoidance, Computational Framework for Predicting Behavioral Therapy Outcome (AAC-BeT)

Sponsor: Laureate Institute for Brain Research, Inc.

Summary

Depression and anxiety disorders rank in the top ten causes of years lived with disability. Less than 50% of patients experiencing long-lasting improvements to current gold-standard treatments. Two gold-standard behavioral interventions include behavioral activation, focused on enhancing approach behavior towards meaningful activities, and exposure-based therapy, focused on decreasing avoidance and challenging negative expectations. While these interventions have divergent treatment targets, there is little knowledge to inform which strategies should be used in the frequent case of comorbid anxiety and depression. Approach-avoidance decision-making paradigms focus on assessing responses when faced with potential rewards and threats, tapping into processes important for both anxiety and depression as well as behavioral activation and exposure-based therapy. For this study, investigators will recruit individuals reporting both anxiety and depression symptoms and randomize them to one of three different interventions: (1) behavioral activation, (2) exposure-based therapy, and a non-specific therapy approach (3) supportive therapy. Participants will complete clinical, self-report, behavioral, and functional magnetic resonance imaging (fMRI) assessments before and after therapy. Investigators will use a computational approach to model factors that may influence one's behavior during approach-avoidance decision-making, including drives to avoid threat versus approach reward and confidence versus uncertainty in one's decisions. This project will accomplish the following aims (1) Determine how changes in brain and behavior responses during approach-avoidance conflict relate to changes in mental health symptoms with the different therapy approaches, (2) Determine the degree to which baseline brain and behavior responses during approach-avoidance conflict predict response to the different therapy approaches, above and beyond the influence of demographics and baseline symptom severity. In addition, by including peripheral blood draws and measures of grace matter volume, the project will also accomplish the following aims: (1) Determine whether kynrenine metabolites measures peripherally may be beneficial as a biomarker of treatment response and (2) determine whether there is an association between change in kynurenine metabolites and changes in gray matter volume with treatment. Results will enhance understanding of how different psychotherapy approaches (behavioral activation, exposure-based therapy) may impact brain responses and decisions when faces with potential reward versus threat and approach versus avoidance drives. In addition, results will have important implications concerning the potential for a more personalized approach to psychotherapy, enhancing knowledge of which types of therapy strategies may be most beneficial for which individuals.

Official title: An Approach-Avoidance, Computational Framework for Predicting Behavioral Therapy Outcome in Anxiety and Depression (AAC-BeT)

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