Internet gaming disorder (IGD) is a serious mental health issue worldwide. A recent meta-analysis including 155 studies in 33 countries reported that the pooled prevalence of IGD among adolescents and young adults is 9.9 %, and this prevalence has been increasing yearly (Gao et al., 2022; Kim et al., 2022). It is regarded as a type of behavioural addiction and was included in section three of the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5), as a disorder (Petry et al., 2014), which is endorsed by the American Psychiatric Association. It is classified as a nonsubstance addiction disorder. The condition arises when an individual spends an extended period of time in virtual cyberspace and becomes strongly dependent on the internet to the point of becoming obsessed or losing control. Numerous studies have shown that individuals with IGD exhibit addictive characteristics similar to those of individuals with drug and gambling addiction. The insufficient inhibition of prefrontal cortex function with abnormal activation of the striatal dopamine system in patients with IGD leads to enhanced craving for gaming cues, similar to the pattern of neural responses in cocaine addiction (Dong and Potenza, 2014). Behavioural studies have shown that impulsive decision-making and risky decision-making deficits in IGD patients are consistent with decision-making biases in heroin dependence, gambling and alcohol addiction, respectively (Sun et al., 2009). The evidence suggests that IGD may share a neurocognitive basis with substance use disorder and gambling disorder (Brand et al., 2019).

IGD is also associated with depression(Burleigh et al., 2018), anxiety(Adams et al., 2019; AJ et al., 2014), and suicidal tendencies(Kuang et al., 2020). Research has revealed that 30–55 % of individuals diagnosed with IGD also exhibit symptoms of depression, with an additional 25–45 % experiencing anxiety symptoms or anxiety disorders. This indicates a comorbid depression rate of 0.32 (95 % confidence interval 0.21–0.43) (Ostinelli et al., 2021). A cross-sectional survey of Asian adolescents revealed that approximately 27.5 % of those with IGD had experienced suicidal thoughts (Cheng et al., 2018; Yu et al., 2024). The findings of the above studies indicate a bidirectional relationship between IGD and other mental health problems, which has the potential to exacerbate the risk of mood disorders (Ostinelli et al., 2021). Therefore, understanding the neural mechanisms of IGD is particularly important for early diagnosis and effective intervention.

Neuroimaging-based magnetic resonance imaging (MRI) is a valuable tool for investigating the pathophysiological mechanism of neurological disorders(Brossollet et al., 2023; Labbé Atenas et al., 2018). Numerous neuroimaging studies have reported functional and structural changes in the brains of individuals with IGD (Niu et al., 2022). Previous studies using structural MRI have shown that patients with IGD have greater gray matter volume in the left thalamus and left cingulate gyrus than healthy controls (HCs) do (Han et al., 2012). These findings may explain the different clinical features of IGD patients and HCs. Another study revealed that the larger volume of the hippocampus and amygdala in IGD patients may be linked to abnormalities in memory processes for game-related cues, and that hippocampal volume is positively correlated with the severity of IGD symptoms (Yoon et al., 2017). In a study of surface-based morphometry, adolescents with IGD presented greater cortical thickness in the bilateral insula and right inferior temporal gyrus and a significant positive correlation between cortical thickness in the left insula and symptom severity (Wang et al., 2018). Yuan et al. also reported decreases in cortical thickness in the orbitofrontal cortex (OFC), insula, parietal cortex, and postcentral gyrus (Yuan et al., 2013). Abnormal changes in gray matter volume in key brain regions, such as the supplementary motor area (SMA) and dorsolateral prefrontal cortex (DLPFC), may be significantly associated with cognitive control impairments in patients with IGD (Wang et al., 2015). Another resting-state functional magnetic resonance imaging (rs-fMRI) study revealed stronger static/dynamic intrinsic local connectivity–regional homogeneity (ReHo) in the bilateral superior frontal gyrus (mSFG), superior frontal gyrus (SFG) and SMA and stronger dynamic ReHo (dReHo) in the left striatal (putamen/caudate) and bilateral thalamic regions in patients with IGD than in HCs. Moreover, the static ReHo (sReHo) values in the left mSFG and SMA as well as dReHo values in the left SMA were positively correlated with IAT scores (Niu et al., 2023). SReHo reflects the spatiotemporal stability of local functional connectivity by calculating the temporal coherence of low-frequency oscillatory signals between neighboring voxels (Zang et al., 2004), whereas dynamic ReHo captures time-varying features of this homogeneity via a sliding time window analysis technique in a task-free state (Liao et al., 2017). The above neuroimaging studies demonstrated that structural and functional abnormalities in the cognitive control and reward-habit systems play key roles in the neurobiological mechanism of IGD.

Using a graph-theoretic approach, degree centrality (DC) counts the number of functional connections of a single node with other nodes within a whole-brain functional network at the voxel level (Farahani et al., 2019; Guye et al., 2010; Sporns, 2018; Wang et al., 2011). This provides a metric indicating the functional network “hub” properties and reflecting the role and status of the node in the brain. An altered DC value indicates abnormal functional synchronization between the node and the rest of the brain, suggesting disrupted function of the corresponding brain region. DC has been widely used in the study of various neuropsychiatric disorders, including schizophrenia (Wheeler et al., 2015; Zhuo et al., 2014), Parkinson's disease (Baggio et al., 2014; Lou et al., 2015), depression (Guo et al., 2022; Li et al., 2017; Yang et al., 2023) and autism (Di Martino et al., 2013), providing new insights into the pattern and complexity of neuropathological mechanisms in a wide range of diseases. To the best of our knowledge, few studies have investigated the DC patterns of the brain in patients with IGD.

Our primary hypothesis is that significant differences in DC might exist in specific brain regions between IGD patients and HCs. Our secondary hypothesis speculated that there is a different FC pattern in the significant brain regions of DC in patients with IGD than in HCs. Therefore, the aim of the present study was to compare the DC values between IGD patients and HCs and identify brain regions with abnormal DC values to investigate the intrinsic dysconnectivity pattern in whole-brain functional networks in patients with IGD. However, voxel-level DC reflects only the local importance of a given voxel in the brain network but cannot provide detailed connectivity information between brain regions(Liao et al., 2013; Smitha et al., 2017). Consequently, we conducted further functional connectivity (FC) analyses using the regions that exhibited significant DC differences as seeds to provide detailed information about connectivity patterns between the regions with abnormal DC and specific regions.