Altered effective connectivity in internet gaming disorder and its predictive value for clinical severity: A spectral DCM study

BACKGROUND: To explore the functionally disordered regions and the directed effective-connectivity relationships among them in Internet Gaming Disorder (IGD), we adopted a meta-analysis-based Dynamic Causal Modeling approach. METHODS: We first performed a meta-analysis of existing rs-fMRI literature using Anisotropic Effect Size Signature Differential Mapping (AES-SDM) to localize the consistent regions with functional changes, which were then defined as regions of interest (ROIs). Next, we collected resting-state fMRI data and IGD-related scale scores from 54 IGD patients and 46 healthy controls, extracted the neuronal time series (BOLD time series) and input them into spectral Dynamic Causal Modeling (spDCM), and characterized between-group changes in effective connectivity (EC) between the ROIs through Parametric Empirical Bayes (PEB) analysis. RESULTS: In the IGD group, SFGdor_R showed reduced inhibitory effective connectivity with IFGopercular_L, IFGorb_L, and INS_R, and IFGorb_L also exhibited attenuated self-inhibition; in addition, an exploratory internally validated prediction analysis suggested that the IFGorb_L self-connection was associated with IAT severity. CONCLUSIONS: These findings indicate altered frontal effective-connectivity patterns consistent with reduced top-down regulatory signaling, rather than definitive evidence of a causal biological mechanism. The internally validated prediction of IAT severity was exploratory, explained a modest proportion of variance, and requires confirmation in larger longitudinal studies with external validation.