multi-domain measures in terms of classification accuracy in a machine learning framework and evaluated the utility of these phenotypic features, especially the reward network connectivity measures. Since recent studies have proposed that resting state fMRI connectivity can potentially serve as one of the key neuroimaging biomarkers for quantitative clinical evaluation of AUD [36,52,53], the findings from the current study may elucidate specific connectivity patterns across reward regions of the brain in abstinent AUD individuals, along with key neuropsychological and impulsivity features, which are distinctly different from healthy controls.
