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.

网络游戏障碍（IGD）被定义为一种特定的行为障碍，与大规模大脑网络之间的异常交互有关。研究人员试图使用静息状态功能连接 (rsFC) 来识别 IGD 中的网络功能障碍。然而，跨研究的结果尚未达成一致，其机制仍不清楚。

本研究旨在通过对 rsFC 研究的荟萃分析来调查 IGD 中的网络功能障碍。包括来自 25 篇出版物（594 名 IGD 患者和 496 名健康对照者）的 22 项基于种子的体素 rsFC 研究。通过根据种子在先前功能网络分区中的位置将种子分类到种子网络中，我们在每个种子网络中执行了多级核密度分析 (MKDA)，以确定哪些大脑系统在 IGD 个体中显示出与特定种子网络的异常交互.

与健康对照组相比，IGD 个体在默认模式网络中表现出显着的低连接性，并且在腹侧注意力网络中默认模式网络和脑岛之间的连接性增强。IGD 还与腹侧注意网络和躯体运动区域之间的连接性增加有关。此外，IGD 组显示边缘网络和额顶网络区域之间的超连接性。

结果表明，患有 IGD 的个体表现出大规模的功能网络改变，这支撑了他们的核心症状，包括情绪能力差、提示反应和渴望、习惯性成瘾行为和执行控制受损。讨论了IGD中是否存在补偿机制，需要进一步研究。该研究结果提供了 IGD 的神经认知网络模型，可作为 IGD 的功能性生物标志物，并具有开发有效诊断和治疗干预的潜力。