Avoidance learning and pain circuit dysfunction in alcohol use disorders

PROJECT SUMMARY / ABSTRACT Alcohol use disorder (AUD) is a chronic debilitating condition that accounts for over half of all substance abuse treatment cases in the United States. Most AUD patients relapse despite treatment. It is increasingly recognized that deficits in avoidance learning are critically involved in motivating habitual and heavy alcohol use. Specifically, due to alcohol’s anxiolytic and analgesic properties, many engage in drinking to avoid painful physical and affective states. Paradoxically, chronic alcohol use is associated with increased pain reactivity and decreased cognitive control. These changes reinforce compulsive drinking as a maladaptive avoidance strategy and further compromise learning of its harmful consequences. Yet, the neural, physiological, and psychological processes inter-relating avoidance learning dysfunction with the maintenance and relapse of AUD remain poorly understood. This K99/R00 proposal addresses this critical gap in research. To this end, we propose to collect functional magnetic resonance imaging (fMRI) data in treatment- seeking AUD patients during a probabilistic learning task which features pain and reward. Our first aim is to characterize dysfunctions of the brain circuits supporting pain reactivity and cognitive control during avoidance learning in AUD patients, as compared to social drinkers. In the second aim, we will evaluate how the neural markers, along with clinical, physiological and behavioral metrics, may be used to (1) diagnostically distinguish clinical characteristics; and (2) model the key pathophysiological pathways that sustain habitual alcohol use. In the third aim, we will identify the risk factors that best predict relapse during the 12-month follow-up, thus offering clinical implications for improving treatment outcomes. The long-term goal of the candidate is to start an independent career in neuroscience research of alcohol addiction. This proposed study will support this goal by serving as a launchpad for the candidate to transition to an independent investigator. The candidate has trained extensively in cognitive neuroscience and devoted himself to the field of addiction neuroscience. By conducting this study, the candidate will broaden his training in the clinical and neurobiological investigation of AUD as well as gain expertise in machine learning and Bayesian modeling. The candidate has identified his training needs and assembled a team of expert mentors for this K99/R00 proposal. The training plan includes structured mentoring, supervised research, formal coursework, presentations at scientific meetings, and professional development. The exceptional research environment and intellectual resources at Yale University will allow the candidate to receive ample guidance, learn novel techniques, and gain independence, while pursuing the research he is passionate about.