Our brain is a network of various regions, and addiction involves intricate interactions among specific brain areas. Research on AUD has revealed significant variability in functional connectivity among regions implicated in executive control, reward processing, motor coordination, and memory consolidation [17–19]. However, functional connectivity does not provide information about the directed casual interactions among brain regions and this limitation calls for a characterization in terms of effective connectivity (EC) [20, 21]. Friston et al. [22] introduced spectral dynamic causal modeling (DCM) using the cross-spectra of the blood oxygenation level dependency (BOLD) signals to estimate dynamic EC in the resting state brain. Subsequently, some studies demonstrated the reliable estimation of intrinsic EC in the absence of external stimulation using spectral DCM [23, 24]. Spectral DCM is widely employed in substance and behavioral addiction research, such as smoking, cocaine, and internet gaming disorder, providing valuable insights into the causal brain mechanisms underlying addiction [25–27]. In contrast to these addictions, the formation and development of AUD are influenced by specific genetic and environmental risk factors [28–30]. One example of an alcohol-specific mechanism is
