Large-scale network dysfunction in youths with Internet gaming disorder: a meta-analysis of resting-state functional connectivity studies

Internet gaming disorder (IGD) has been defined as a specific behavioral disorder, associated with abnormal interactions among large-scale brain networks. Researchers have sought to identify the network dysfunction in IGD using resting-state functional connectivity (rsFC). However, results across studies have not reached an agreement yet and the mechanism remains unclear. The present research aimed to investigate network dysfunction in IGD through a meta-analysis of rsFC studies. Twenty-two seed-based voxel-wise rsFC studies from 25 publications (594 individuals with IGD and 496 healthy controls) were included. By categorizing seeds into seed-networks based on their location within a prior functional network parcellations, we performed a Multilevel kernel density analysis (MKDA) within each seed-network to identify which brain systems showed abnormal interaction with particular seed-network in individuals with IGD. Compared to healthy control groups, individuals with IGD exhibited significant hypoconnectivity within the default mode network, and enhanced connectivity between the default mode network and insula within the ventral attention network. IGD was also associated with increased connectivity between the ventral attention network and somatomotor regions. Furthermore, the IGD groups showed hyperconnectivity between the limbic network and regions of the frontoparietal network. The results suggest that individuals with IGD show large-scale functional network alteration which underpins their core symptoms including poor emotional competence, cue-reactivity and craving, habitual addictive behaviors and impaired executive control. Whether the compensation mechanism exists in IGD is discussed, and further research is needed. The findings provide a neurocognitive network model of IGD, which may serve as functional biomarkers for IGD and have potentials for development of effective diagnosis and therapeutic interventions.