Neural Signature Changes Across Early Abstinence in Alcohol Use Disorder

PROJECT SUMMARY/ABSTRACT Alcohol use accounts for 1 in 5 deaths of individuals aged 20 to 49-years old, and Alcohol Use Disorder (AUD) is associated with deficits in brain structure and function, but it remains unclear which of these brain abnormalities can recover when alcohol use stops. Understanding brain changes associated with early

abstinence occurring through evidence-based residential treatment may offer insights into the biological basis of AUD and potential therapeutic targets. This proposal aims to fill a gap in understanding how the neural mechanisms associated with cognitive reappraisal (e.g., prefrontal cortex [PFC]) and alcohol cue reactivity

(e.g., striatum) change during early abstinence, and whether changes in these mechanisms can predict the individuals most likely to return to heavy alcohol use. We and others have shown that, relative to healthy adults, individuals with AUD have greater difficulties with emotion regulation and greater craving and alcohol

cue reactivity. Yet, it remains unclear how abstinence affects brain function during reappraisal and cue reactivity, and how this relates to risk for future alcohol use. Here, we propose to study patients with AUD (N = 150) engaged in ecologically-valid residential treatment to determine the neural mechanisms that change

during early abstinence and if they indicate risk for return to heavy drinking. We will assess these individuals using fMRI within 4 days of admission to treatment and again within 2 days before discharge. We will also follow participants for 6 months to assess frequency of heavy drinking. We will use cutting-edge analytic

techniques to maximize our ability to observe differences. Specifically, we will use multivariate pattern analysis to quantify neural signatures of reappraisal and cue reactivity. We and others have developed models can accurately identify brain activation associated with a) cognitive reappraisal and b) cue reactivity to drug stimuli.

These processes likely reflect circuit-driven neural underpinnings, thus in addition to neural signatures we will examine connectivity between PFC and subcortical regions linked to craving and emotional reactivity. We can then use machine learning algorithms to identify relationships between neural signatures, connectivity, and

variables associated with relapse risk, such as craving and poor emotional coping skills. We will use these models to test our central hypothesis that neural function associated with reappraisal and alcohol cue reactivity will change across abstinence and indicate likelihood of treatment success. Specific Aims are to 1) determine

how neural mechanisms related to reappraisal and alcohol cue-reactivity change across early abstinence during treatment, 2) determine how circuit strength between the PFC and subcortical regions change across early abstinence, and 3) identify neuroimaging variables that prospectively predict return to heavy drinking. The

proposal will improve understanding of the neural mechanisms that may recover with reduced drinking levels and whether neural function indicates long-term success.