Taken together, studies from multiple domains of neural features have established both structural and functional abnormalities in individuals with AUD. The findings from these studies converge to emphasize the importance of understanding brain networks affected in AUD, and therefore numerous recent studies have attempted to elucidate network mechanisms and dysfunctions underlying AUD by studying functional connectivity. However, there is a critical lack of studies examining functional connectivity using neurophysiological sources, and the current study attempts to fill the gap in knowledge by examining EEG source functional connectivity of the DMN, the most studied resting network, in addition to identifying other relevant features that are characteristic of AUD (e.g., measures of neuropsychological function and impulsivity). The a priori hypothesis of the current study is that individuals with AUD will show distinct and differential patterns in DMN functional connectivity, neuropsychological measures, and impulsivity factors, compared to unaffected controls, as elicited by a classification algorithm such as Random Forest [36]. We expect that the RF algorithm will identify specific connections in different frequency bands across the DMN nodes, especially in frontal regions and
