Developing a mechanistic neurobiological model of exposure therapy response based on fear extinction theory

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Project Summary I am applying for a Mentored Patient-Oriented Career Development Award (K23) to support my development into an independently funded translational clinical psychologist. My long-term career goal is to conduct a program of research that translates neurobiological models of anxiety and its treatment into guidance for real- life clinical decision-making. Currently, although exposure therapy is the best available treatment for anxiety disorders, 25% of patients do not respond to an adequate course of exposure therapy and we do not know why. A critical long-term goal is to improve exposure therapy response by tailoring therapy based on the neurobiological profile of each patient. Because the mechanism of exposure therapy is thought to be extinction learning, the proposed research aims to address this goal by directly linking exposure therapy response to extinction learning in a sample of adults with social anxiety disorder. Specifically, I aim to identify neurobiological features of extinction learning that predict successful recall, are associated with clinical symptoms, and predict therapy response. The project will use a paradigm that I developed and piloted to assess physiological and neuroimaging measures of extinction learning. The expected outcomes are an innovative mechanistic neurobiological model that can identify patients at risk of non-response, as well as specific, testable hypotheses for how to improve outcomes for these patients. In order for this project, and my broader career goals, to succeed, it is imperative that I have expertise related to exposure therapy, predictive modeling, analysis of self-report, physiological, and fMRI data, and traditional and biomarker-guided clinical trial designs. I already have expertise in the theory and implementation of exposure therapy, as well as the analysis of self-report and fMRI data. This K23 award would allow me to receive advanced training in (1) machine learning techniques for building and evaluating clinically relevant predictive models, (2) specific skills for analysis and interpretation of physiological data, and (3) traditional and biomarker-guided clinical trials. I have assembled an inter-disciplinary team of mentors at Stanford University that are ideally suited to guide my research and training. Dr. Leanne Williams (primary mentor, Department of Psychiatry) will provide expertise on using neurobiology to make treatment outcome predictions, and provide overall career development mentorship throughout the project. Dr. James Gross (co-mentor, Department of Psychology) will provide expertise on physiological data and its integration with self-report and fMRI data. Dr. Tze Lai (co-mentor, Department of Statistics) will provide expertise on predictive models and biomarker-guided clinical trial designs. The training and associated research will take place in the Psychiatry and Behavioral Sciences Department at Stanford University, a world renowned hub of neuroscience and psychiatry research, and at Stanford's Center for Cognitive and Neurobiological Imaging, a state-of-the-art neuroimaging facility.