The primary purpose of this study was to investigate the specific brain regions that contribute significantly to the classification of individuals with AUD from healthy controls (HCs), utilizing a ReHo-based MVPA approach. We hypothesized that executive control, decision-making, and reward/loss processing-related brain regions would exhibit the greatest contribution to classification accuracy. The second purpose was to investigate the neural mechanisms underlying AUD and identify the potential clinical biomarkers associated with AUD by assessing the EC among the brain regions that provide the most information features for the classification. We hypothesized that individuals with AUD exhibit an atypical pattern of EC among brain regions implicated in executive control and reward/loss processing, and that these aberrant connectivities are associated with symptoms of both obsessive-compulsive behavior and impulsivity. The third purpose of this study was to evaluate the accuracy and reliability of a classification model that utilizes ReHo values and machine learning techniques in distinguishing between individuals with AUD and HCs, using two independent datasets. The fourth purpose was to investigate the personality traits that render individuals susceptible to alcohol use and the development of AUD. We postulated that impulsivity and compulsivity may constitute crucial personality traits in diagnosing AUD.
