processing networks. Thus, although neurophysiological markers of AUD at the finer time scale of neural communication can uncover subtle, sensitive, real-time, ongoing neurocognitive dynamics [60,61,62], they remain largely unknown due to paucity of studies. Thus, the current study is the first to fill this gap to examine eLORETA-based DMN FC features to classify individuals with AUD from unaffected controls by applying the RF model to a relatively larger sample of individuals with AUD (N = 30). Further, in order to improve the prediction accuracy of the RF model, in addition to the neural connectivity features, it is important to include other characteristic features of AUD, such as neurocognitive performance and impulsivity, as the individuals with AUD are also known to manifest a range of neuropsychological impairments [63,64] and heightened impulsivity [65]. Therefore, the RF model in the current study will use features from all three domains (i.e., EEG FC, neurocognition, and impulsivity).
