Deficient dynamics of prefrontal-striatal and striatal-default mode network (DMN) neural circuits in internet gaming disorder

Background: Studies have proven that individuals with internet gaming disorder (IGD) show impaired cognitive control over game craving; however, the neural mechanism underlying this process remains unclear. Accord-ingly, the present study aimed to investigate the dynamic features of brain functional networks of individuals with IGD during rest, which have barely been understood until now. Methods: Resting-state fMRI data were collected from 333 subjects (123 subjects with IGD (males/females: 73/ 50) and 210 healthy controls (males/females: 135/75)). First, the data-driven methodology, named co-activation pattern analysis, was applied to investigate the dynamic features of nucleus accumbens (the core region involved in craving/reward processing and addiction)-centered brain networks in IGD. Further, machine learning analysis was conducted to investigate the prediction effect of the dynamic features on participants' addiction severity.Results: Compared to controls, subjects in the IGD group showed decreased resilience, betweenness centrality and occurrence in the prefrontal-striatal neural circuit, and decreased in-degree in the striatal-default mode network (DMN) circuit. Moreover, these decreased dynamic features could significantly predict participants' addiction severity.Limitations: The causal relationship between IGD and the abnormal dynamic features cannot be identified in this study. All the subjects were university students.Conclusions: The present results revealed the underlying brain networks of uncontrollable craving and game -seeking behaviors in individuals with IGD during rest. The decreased dynamics of the prefrontal-striatal and striatal-DMN neural circuits might be potential biomarkers for predicting the addiction severity of IGD and potential targets for effective interventions to reduce game craving of this disorder.