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Abstract

Objectives

Understanding the neural mechanisms underlying Internet gaming disorder (IGD) is essential for the condition's diagnosis and treatment. Nevertheless, the pathological mechanisms of IGD remain elusive at present. Hence, we employed multi-voxel pattern analysis (MVPA) and spectral dynamic causal modeling (spDCM) to explore this issue.

Methods

Resting-state fMRI data were collected from 103 IGD subjects (male = 57) and 99 well-matched recreational game users (RGUs, male = 51). Regional homogeneity was calculated as the feature for MVPA based on the support vector machine (SVM) with leave-one- out cross-validation. Mean time series data extracted from the brain regions in accordance with the MVPA results were used for further spDCM analysis.

Results

Results display a high accuracy of 82.67% (sensitivity of 83.50% and specificity of 81.82%) in the classification of the two groups. The most discriminative brain regions that contributed to the classification were the bilateral parahippocampal gyrus (PG), right anterior cingulate cortex (ACC), and middle frontal gyrus (MFG). Significant correlations were found between addiction severity (IAT and DSM scores) and the ReHo values of the brain regions that contributed to the classification. Moreover, the results of spDCM showed that compared with RGU, IGD showed decreased effective connectivity from the left PG to the right MFG and from the right PG to the ACC and decreased self-connection in the right PG.

Conclusions

These results show that the weakening of the PG and its connection with the prefrontal cortex, including the ACC and MFG, may be an underlying mechanism of IGD.

Open access

Abstract

Background and aims

Individuals with addictive disorders are usually characterized by impaired executive control, persistent craving and excessive reward-seeking. However, it is unclear whether there is a deviation in the connection pattern among the neural systems implicated in these problem behaviors.

Methods

One hundred thirty-six online gaming players were recruited in the current study (68 Internet gaming disorder (IGD) subjects and 68 recreational game users (RGUs) who served as controls matched on age, sex, years of education, and years of gaming). Dynamic interactions among the reward system (striatum), control system (prefrontal cortex), and the interoceptive awareness system (insula) were calculated and compared when subjects were facing gaming cues.

Results

The results revealed that RGUs showed a significant positive correlation in the putamen-middle frontal gyrus (MFG)-insula neural pathway when facing gaming cues, which was missing in the IGD subjects. Additionally, dynamic causal modeling (DCM) analysis revealed that the MFG region was more inhibited by the putamen in the IGD subjects relative to the RGUs.

Conclusions

These findings suggest that the inhibitory neuromodulation of the putamen to the prefrontal cortex in IGD individuals undermines the balance among the tripartite systems. Our findings provide novel neurobiological evidence for understanding the internal connection bias of the addicted individual’s neural system and how the addictive disorder impairs executive control; consequently, the pathway from the striatum to the prefrontal cortex may serve as a potential biomarker to predict the risk of developing an addiction.

Open access
Journal of Behavioral Addictions
Authors:
Wei-Ran Zhou
,
Min Wang
,
Hao-Hao Dong
,
Zhaojie Zhang
,
Xiaoxia Du
,
Marc N. Potenza
, and
Guang-Heng Dong

Abstract

Background

Internet gaming disorder (IGD) is a type of behavioral addiction characterized by poorly controlled and interfering patterns of game playing. Studies have suggested that the IGD is usually accompanied by increased desire or craving for gaming, suggesting that secondary rewards related to gaming may become more salient than those for primary rewards like food. However, this hypothesis has not been formally tested and potential neural mechanisms remain unclear.

Methods

This is a functional magnetic resonance imaging (fMRI) study. Twenty-one IGD subjects and 23 matched individuals with recreational game use (RGU) were scanned when exposed to gaming (secondary rewards), food (primary rewards) and neutral cues. Group-by-cue-type interaction analyses and subsequent within-group analyses for fMRI data were performed and seed-based functional connectivity (FC) analyses explored further potential neural features.

Results

IGD subjects’ subjective craving responses to gaming cues were higher than to food cues, while the opposite was observed in RGU subjects. Group-by-cue interaction effects implicated the precuneus and precuneus-caudate FC. Simple effect analysis showed that for IGD subjects, gaming-related cues elicited higher FC in precuneus-caudate relationships than did food-related cues. In the RGU subjects, the opposite was observed. Significant correlations were found between brain features and craving scores.

Conclusions

These results support the hypothesis regarding imbalances in sensitivities to different types of reward in IGD, and suggest neural mechanisms by which craving for gaming may make secondary rewards more salient than primary ones, thus promoting participation in addictive patterns of gaming.

Open access

Abstract

Background

Although previous studies have revealed gender-related differences in executive function in internet gaming disorder (IGD), neural mechanisms underlying these processes remain unclear, especially in terms of brain networks.

Methods

Resting-state fMRI data were collected from 78 subjects with IGD (39 males, 20.8 ± 2.16 years old) and 72 with recreational game use (RGU) (39 males, 21.5 ± 2.56 years old). By utilizing graph theory, we calculated participation coefficients among brain network modules for all participants and analyzed the diagnostic-group-by-gender interactions. We further explored possible causal relationships between networks through spectral dynamic causal modeling (spDCM) to assess differences in between-network connections.

Results

Compared to males with RGU, males with IGD demonstrated reduced modular segregation of the frontal-parietal network (FPN). Male IGD subjects also showed increased connections between the FPN and cingulo-opercular network (CON); however, these differences were not found in female subjects. Further spDCM analysis indicated that the causal influence from CON to FPN in male IGD subjects was enhanced relative to that of RGU males, while this influence was relatively reduced in females with IGD.

Conclusions

These results suggest poor modular segmentation of the FPN and abnormal FPN/CON connections in males with IGD, suggesting a mechanism for male vulnerability to IGD. An increased “bottom-up” effect from the CON to FPN in male IGD subjects could reflect dysfunction between the brain networks. Different mechanisms may underlie in IGD, suggesting that different interventions may be optimal in males and females with IGD.

Open access

Abstract

Background

Internet gaming disorder (IGD) is included in the DSM-5 as a provisional diagnosis. Whether IGD should be regarded as a disorder and, if so, how it should be defined and thresholded have generated considerable debate.

Methods

In the current study, machine learning was used, based on regional and interregional brain features. Resting-state data from 374 subjects (including 148 IGD subjects with DSM-5 scores ≥5 and 93 IGD subjects with DSM-5 scores ≥6) were collected, and multivariate pattern analysis (MVPA) was employed to classify IGD from recreational game use (RGU) subjects based on regional brain features (ReHo) and communication between brain regions (functional connectivity; FC). Permutation tests were used to assess classifier performance.

Results

The results demonstrated that when using DSM-5 scores ≥5 as the inclusion criteria for IGD subjects, MVPA could not differentiate IGD subjects from RGU, whether based on ReHo or FC features or by using different templates. MVPA could differentiate IGD subjects from RGU better than expected by chance when using DSM-5 scores ≥6 with both ReHo and FC features. The brain regions involved in the default mode network and executive control network and the cerebellum exhibited high discriminative power during classification.

Discussion

The current findings challenge the current IGD diagnostic criteria thresholding proposed in the DSM-5, suggesting that more stringent criteria may be needed for diagnosing IGD. The findings suggest that brain regions involved in the default mode network and executive control network relate importantly to the core criteria for IGD.

Open access