White matter integrity of right frontostriatal circuit predicts internet addiction severity among internet gamers.

Excessive use of the internet, which is a typical scenario of self-control failure, could lead to potential consequences such as anxiety, depression, and diminished academic performance. However, the underlying neuropsychological mechanisms remain poorly understood. This study aims to investigate the structural basis of self-control and internet addiction. In a cohort of 96 internet gamers, we examined the relationships among grey matter volume and white matter integrity within the frontostriatal circuits and internet addiction severity, as well as self-control measures. The results showed a significant and negative correlation between dACC grey matter volume and internet addiction severity (p < 0.001), but not with self-control. Subsequent tractography from the dACC to the bilateral ventral striatum (VS) was conducted. The fractional anisotropy (FA) and radial diffusivity of dACC-right VS pathway was negatively (p = 0.011) and positively (p = 0.020) correlated with internet addiction severity, respectively, and the FA was also positively correlated with self-control (p = 0.036). These associations were not observed for the dACC-left VS pathway. Further mediation analysis demonstrated a significant complete mediation effect of self-control on the relationship between FA of the dACC-right VS pathway and internet addiction severity. Our findings suggest that the dACC-right VS pathway is a critical neural substrate for both internet addiction and self-control. Deficits in this pathway may lead to impaired self-regulation over internet usage, exacerbating the severity of internet addiction.

Identification of patients with internet gaming disorder via a radiomics-based machine learning model of subcortical structures in high-resolution T1-weighted MRI.

It is of vital importance to establish an objective and reliable model to facilitate the early diagnosis and intervention of internet gaming disorder (IGD). A total of 133 patients with IGD and 110 healthy controls (HCs) were included. We extracted radiomic features of subcortical structures in high-resolution T1-weighted MRI. Different combinations of four feature selection methods (analysis of variance, Kruskal-Wallis, recursive feature elimination and relief) and ten classification algorithms were used to identify the most robust combined models for distinguishing IGD patients from HCs. Furthermore, a nomogram incorporating radiomic signatures and independent clinical factors was developed. Calibration curve and decision curve analyses were used to evaluate the nomogram. The combination of analysis of variance selector and logistic regression classifier identified that the radiomic model constructed with 20 features from the right caudate nucleus and amygdala showed better IGD screening performance. The radiomic model produced good areas under the curves (AUCs) in the training, validation and test cohorts (AUCs of 0.961, 0.903 and 0.895, respectively). In addition, sex, internet addiction test scores and radiomic scores were included in the nomogram as independent risk factors for IGD. Analysis of the correction curve and decision curve showed that the clinical-radiomic model has good reliability (C-index: 0.987). The nomogram incorporating radiomic features of subcortical structures and clinical characteristics achieved satisfactory classification performance and could serve as an effective tool for distinguishing IGD patients from HCs.

Wanting-liking dissociation and altered dopaminergic functioning: Similarities between internet gaming disorder and tobacco use disorder.

Background: Although internet gaming disorder (IGD) has been included in the DSM-5 for approximately 10 years, debate remains regarding its existence and classification. Methods: The current research incorporated three approaches. First, implicit association tests were used to examine for potential dissociation between wanting and liking in IGD. Second, brain features in wanting and liking circuits were tested and compared with tobacco use disorder (TUD) when performing a cue-craving task to explore the neural features of wanting and liking. Third, dopaminergic systems were investigated in IGD and TUD using neuromelanin-sensitive MRI. Results: The implicit association test results supported a wanting-liking dissociation in IGD participants. Functional MRI data suggested neural correlates underlying wanting-liking dissociation in IGD and TUD participants, with positive correlations suggesting greater dissociation with increasing addiction severity. Neuromelanin results suggest dopaminergic differences in IGD and TUD relative to healthy control participants. Conclusions: A wanting-liking dissociation in IGD participants suggests gaming motivations in IGD relating to incentive sensitization rather than hedonic responses. The neuromelanin-sensitive MRI results suggest dopaminergic involvement in IGD and TUD. The findings suggest similar brain-behaviour mechanisms for IGD and TUD based on an incentive-sensitization model for addiction, having implications for potential therapeutic strategies and policy-based interventions.

Effects of bilateral tDCS over DLPFC on response inhibition, craving, and brain functional connectivity in Internet gaming disorder: A randomized, double-blind, sham-controlled trial with fMRI.

Background and aims: Impaired inhibitory control accompanied by enhanced craving is hallmark of addiction. This study investigated the effects of transcranial direct current stimulation (tDCS) on response inhibition and craving in Internet gaming disorder (IGD). We examined the brain changes after tDCS and their correlation with clinical variables. Methods: Twenty-four males with IGD were allocated randomly to an active or sham tDCS group, and data from 22 participants were included for analysis. Participants self-administered bilateral tDCS over the dorsolateral prefrontal cortex (DLPFC) for 10 sessions. Stop-signal tasks were conducted to measure response inhibition and participants were asked about their cravings for Internet gaming at baseline and post-tDCS. Functional magnetic resonance imaging data were collected at pre- and post-tDCS, and group differences in resting-state functional connectivity (rsFC) changes from the bilateral DLPFC and nucleus accumbens were examined. We explored the relationship between changes in the rsFC and behavioral variables in the active tDCS group. Results: A significant group-by-time interaction was observed in response inhibition. After tDCS, only the active group showed a decrease in the stop-signal reaction time (SSRT). Although craving decreased, there were no significant group-by-time interactions or group main effects. The anterior cingulate cortex (ACC) showed group differences in post- versus pre-tDCS rsFC from the right DLPFC. The rsFC between the ACC and left middle frontal gyrus was negatively correlated with the SSRT. Discussion and conclusion: Our study provides preliminary evidence that bilateral tDCS over the DLPFC improves inhibitory control and could serve as a therapeutic approach for IGD.

The severity of addiction mediates loneliness and cortical volume in internet gaming disorder.

Internet gaming disorder (IGD) subjects reported higher loneliness scores than healthy controls. However, the neural correlates underlying the association between loneliness and IGD remain unclear. Thus, the aim of this study was to explore the relationship between loneliness, online gaming addiction and brain structure. In the current study, structural MRI data were acquired from 84 IGD subjects and 103 matched recreational game users (RGUs). We assessed and compared their addiction severity, loneliness scores, and cortical volumes and analyzed the correlations among these values. Significant correlations were found between loneliness scores and brain volumes in the postcentral cortex, the medial orbitofrontal cortex, the rostral anterior cingulate cortex, and the temporal cortex. In addition, the addiction severity scores partly mediated the relationship between loneliness score and cortical volume in IGD. The results showed that participants with extreme loneliness had significant correlations with brain regions responsible for executive control, social threat surveillance and avoidance. More importantly, the severity of addiction mediates loneliness and cortical volume. The findings shed new insight into the neural mechanisms of loneliness and IGD and have implications for potential treatment.

Static and dynamic changes of intrinsic brain local connectivity in internet gaming disorder.

BACKGROUND: Studies have revealed that intrinsic neural activity varies over time. However, the temporal variability of brain local connectivity in internet gaming disorder (IGD) remains unknown. The purpose of this study was to explore the alterations of static and dynamic intrinsic brain local connectivity in IGD and whether the changes were associated with clinical characteristics of IGD. METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) scans were performed on 36 individuals with IGD (IGDs) and 44 healthy controls (HCs) matched for age, gender and years of education. The static regional homogeneity (sReHo) and dynamic ReHo (dReHo) were calculated and compared between two groups to detect the alterations of intrinsic brain local connectivity in IGD. The Internet Addiction Test (IAT) and the Pittsburgh Sleep Quality Index (PSQI) were used to evaluate the severity of online gaming addiction and sleep quality, respectively. Pearson correlation analysis was used to evaluate the relationship between brain regions with altered sReHo and dReHo and IAT and PSQI scores. Receiver operating characteristic (ROC) curve analysis was used to reveal the potential capacity of the sReHo and dReHo metrics to distinguish IGDs from HCs. RESULTS: Compared with HCs, IGDs showed both increased static and dynamic intrinsic local connectivity in bilateral medial superior frontal gyrus (mSFG), superior frontal gyrus (SFG), and supplementary motor area (SMA). Increased dReHo in the left putamen, pallidum, caudate nucleus and bilateral thalamus were also observed. ROC curve analysis showed that the brain regions with altered sReHo and dReHo could distinguish individuals with IGD from HCs. Moreover, the sReHo values in the left mSFG and SMA as well as dReHo values in the left SMA were positively correlated with IAT scores. The dReHo values in the left caudate nucleus were negatively correlated with PSQI scores. CONCLUSIONS: These results showed impaired intrinsic local connectivity in frontostriatothalamic circuitry in individuals with IGD, which may provide new insights into the underlying neuropathological mechanisms of IGD. Besides, dynamic changes of intrinsic local connectivity in caudate nucleus may be a potential neurobiological marker linking IGD and sleep quality.

Brain responses to decision-making in easy and hard choices in internet gaming disorder: Implications for irrepressible gaming behaviours.

BACKGROUND: Impaired decision-making was observed in internet gaming disorder (IGD), however, these studies did not differentiate 'hard' to 'easy' decisions, and only the 'hard' decision-making could reveal the mechanism underlying this issue. METHODS: We recruited forty-eight individuals with IGD and forty-six recreational internet game users (RGUs) as a control group in this study. fMRI data were collected when they were finishing a value-matching delayed discount task (DDT), which included easy and hard decisions judging based on the indifference points of every participant. The correlations between brain responses during DDT and IGD severity and the effective connectivity between brain regions were calculated. RESULTS: Compared to RGUs, IGD subjects showed enhanced activation in the orbitofrontal cortex (OFC) when facing hard choices, and this feature was associated with IGD severity. In addition, individuals with IGD showed increased effective connectivity from the OFC to the dorsolateral prefrontal cortex and the OFC to the occipital lobe and decreased effective connectivity from the occipital lobe to the OFC. CONCLUSION: The current study showed that the abnormal activation in the OFC was associated with IGD severity and higher OFC-DLPFC/OFC-occipital lobe effective connectivity and lower occipital lobe-OFC effective connectivity when individuals with IGD faced different choices in the DDT. These findings suggest the neural mechanisms of impulsive decision-making in individuals with IGD due to dysfunction with subjective evaluation and dysfunction of the connection with the executive control system.

Reduced loss aversion in value-based decision-making and edge-centric functional connectivity in patients with internet gaming disorder.

Background and aims: Impaired value-based decision-making is a feature of substance and behavioral addictions. Loss aversion is a core of value-based decision-making and its alteration plays an important role in addiction. However, few studies explored it in internet gaming disorder patients (IGD). Methods: In this study, IGD patients (PIGD) and healthy controls (Con-PIGD) performed the Iowa gambling task (IGT), under functional magnetic resonance imaging (fMRI). We investigated group differences in loss aversion, brain functional networks of node-centric functional connectivity (nFC) and the overlapping community features of edge-centric functional connectivity (eFC) in IGT. Results: PIGD performed worse with lower average net score in IGT. The computational model results showed that PIGD significantly reduced loss aversion. There was no group difference in nFC. However, there were significant group differences in the overlapping community features of eFC1. Furthermore, in Con-PIGD, loss aversion was positively correlated with the edge community profile similarity of the edge2 between left IFG and right hippocampus at right caudate. This relationship was suppressed by response consistency3 in PIGD. In addition, reduced loss aversion was negatively correlated with the promoted bottom-to-up neuromodulation from the right hippocampus to the left IFG in PIGD. Discussion and conclusions: The reduced loss aversion in value-based decision making and their related edge-centric functional connectivity support that the IGD showed the same value-based decision-making deficit as the substance use and other behavioral addictive disorders. These findings may have important significance for understanding the definition and mechanism of IGD in the future.

Internet gaming disorder and tobacco use disorder share neural connectivity patterns between the subcortical and the motor network.

Internet gaming disorder (IGD) and tobacco use disorder (TUD) are globally common, non-substance-related disorders and substance-related disorders worldwide, respectively. Recognizing the commonalities between IGD and TUD will deepen understanding of the underlying mechanisms of addictive behavior and excessive online gaming. Using node strength, 141 resting-state data were collected in this study to compute network homogeneity. The participants included participants with IGD (PIGD: n = 34, male = 29, age: 15-25 years), participants with TUD (PTUD: n = 33, male = 33, age: 19-42 years), and matched healthy controls (control-for-IGD: n = 41, male = 38, age: 17-32 years; control-for-TUD: n = 33, age: 21-27 years). PIGD and PTUD exhibited common enhanced node strength between the subcortical and motor networks. Additionally, a common enhanced resting-state functional connectivity (RSFC) was found between the right thalamus and right postcentral gyrus in PIGD and PTUD. Node strength and RSFC were used to distinguish PIGD and PTUD from their respective healthy controls. Interestingly, models trained on PIGD versus controls could classify PTUD versus controls and vice versa, suggesting that these disorders share common neurological patterns. Enhanced connectivity may indicate a greater association between rewards and behaviors, inducing addiction behaviors without flexible and complex regulation. This study discovered that the connectivity between the subcortical and motor networks is a potential biological target for developing addiction treatment in the future.

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. Accordingly, 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.

Subgroups of internet gaming disorder based on addiction-related resting-state functional connectivity.

AIMS: To identify subgroups of people with internet gaming disorder (IGD) based on addiction-related resting-state functional connectivity and how these subgroups show different clinical correlates and responses to treatment. DESIGN: Secondary analysis of two functional magnetic resonance imaging (fMRI) data sets. SETTING: Zhejiang province and Beijing, China. PARTICIPANTS: One hundred and sixty-nine IGD and 147 control subjects. MEASUREMENTS: k-Means algorithmic and support-vector machine-learning approaches were used to identify subgroups of IGD subjects. These groups were examined with respect to assessments of craving, behavioral activation and inhibition, emotional regulation, cue-reactivity and guessing-related measures. FINDINGS: Two groups of subjects with IGD were identified and defined by distinct patterns of connectivity in brain networks previously implicated in addictions: subgroup 1 ('craving-related subgroup') and subgroup 2 ('mixed psychological subgroup'). Clustering IGD on this basis enabled the development of diagnostic classifiers with high sensitivity and specificity for IGD subgroups in 10-fold validation (n = 218) and out-of-sample replication (n = 98) data sets. Subgroup 1 is characterized by high craving scores, cue-reactivity during fMRI and responsiveness to a craving behavioral intervention therapy. Subgroup 2 is characterized by high craving, behavioral inhibition and activations scores, non-adaptive emotion-regulation strategies and guessing-task fMRI measures. Subgroups 1 and 2 showed largely opposite functional-connectivity patterns in overlapping networks. CONCLUSIONS: There appear to be two subgroups of people with internet gaming disorder, each associated with differing patterns of brain functional connectivity and distinct clinical symptom profiles and gender compositions.

Disrupted dynamic network reconfiguration of the executive and reward networks in internet gaming disorder.

BACKGROUND: Studies have shown that people with internet gaming disorder (IGD) exhibit impaired executive control of gaming cravings; however, the neural mechanisms underlying this process remain unknown. In addition, these conclusions were based on the hypothesis that brain networks are temporally static, neglecting dynamic changes in cognitive processes. METHODS: Resting-state fMRI data were collected from 402 subjects [162 subjects with IGD and 240 recreational game users (RGUs)]. The community structure (recruitment and integration) of the executive control network (ECN) and the basal ganglia network (BGN), which represents the reward network, of patients with IGD and RGUs were compared. Mediation effects among the different networks were analyzed. RESULTS: Compared to RGUs, subjects with IGD had a lower recruitment coefficient within the right ECN. Further analysis showed that only male subjects had a lower recruitment coefficient. Mediation analysis showed that the integration coefficient of the right ECN mediated the relationship between the recruitment coefficients of both the right ECN and the BGN in RGUs. CONCLUSIONS: Male subjects with IGD had a lower recruitment coefficient than RGUs, which impairing their impulse control. The mediation results suggest that top-down executive control of the ECN is absent in subjects with IGD. Together, these findings could explain why subjects with IGD exhibit impaired executive control of gaming cravings; these results have important therapeutic implications for developing effective interventions for IGD.

Sex differences in neural substrates of risk taking: Implications for sex-specific vulnerabilities to internet gaming disorder.

Background and aims: Sex differences in internet gaming disorder (IGD) remain unknown. Investigating sex-specific neural features that underlie the core risk factor (i.e., risk-taking) of IGD would help in understanding sex-specific vulnerabilities to IGD and advance sex-specific treatments and prevention for IGD. Methods: 111 participants (28 IGD males, 27 IGD females, 26 recreational game user (RGU) males, 30 RGU females) completed a probability discounting task during fMRI scanning. Results: First, among RGUs, males showed a higher risk-taking tendency and greater neural activation associated with risk/value evaluation for reward (the ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC), left putamen) and smaller activation associated with cognitive control (the inferior frontal gyrus) than females during the contrast of risky-safe choices. Moreover, males showed a greater modulatory effect of risky choices on the connection from the vmPFC/ACC to the left putamen than females. Second, IGD males showed decreased activation in the vmPFC/ACC and left putamen compared to RGU males, whereas this decrease did not exist in IGD females. Discussion: Males show a higher risk-taking tendency than females. Altered neural substrates associated with risky decision-making exist in IGD males but not in IGD females. Conclusions: The present findings fill the gap in information on the behavioral and neural substrates underlying IGD among females and demonstrate that a high risk-taking tendency is a risk factor and core symptom only in IGD males but not in IGD females. It is necessary to design and adopt distinct treatments and prevention strategies for IGD in males and females.

Predicting the severity of internet gaming disorder with resting-state brain features: A multi-voxel pattern analysis.

BACKGROUND: Internet gaming disorder (IGD) has become a worldwide mental health concern; however, the neural mechanism underlying this disorder remains unclear. Multivoxel pattern analysis (MVPA), a newly developed data-driven approach, can be used to investigate the neural features of IGD based on massive neural data. METHODS: Resting-state fMRI data from four hundred and two participants with varying levels of IGD severity were recruited. Regional homogeneity (ReHo) and the amplitude of low-frequency fluctuation (ALFF) were calculated and subsequently decoded by applying MVPA. The highly weighted regions in both predictive models were selected as regions of interest for further graph theory and Granger causality analysis (GCA) to explore how they affect IGD severity. RESULTS: The results revealed that the neural patterns of ReHo and ALFF can independently and significantly predict IGD severity. The highly weighted regions that contributed to both predictive models were the right precentral gyrus and left postcentral gyrus. Moreover, topological properties of the right precentral gyrus were significantly correlated with IGD severity; further GCA revealed effective connectivity from the right precentral gyrus to left precentral gyrus and dorsal anterior cingulate cortex, both of which were significantly associated with IGD severity. CONCLUSIONS: The present study demonstrated that IGD has distinctive neural patterns, and this pattern could be found by machine learning. In addition, the neural features in the right precentral gyrus play a key role in predicting IGD severity. The current study revealed the neural features of IGD and provided a potential target for IGD interventions using brain modulation.

Aberrant intrinsic neural network strength in individuals with "smartphone addiction": An MRI data fusion study.

BACKGROUND AND OBJECTIVES: Excessive smartphone use, also referred to as "smartphone addiction" (SPA), has increasingly attracted neuroscientific interest due to its similarities with other behavioral addictions, particularly internet gaming disorder. Little is known about the neural mechanisms underlying smartphone addiction. We explored interrelationships between brain structure and function to specify neurobiological correlates of SPA on a neural system level. METHODS: Gray matter volume (GMV) and intrinsic neural activity (INA) were investigated in individuals with SPA (n = 20) and controls (n = 24), using multimodal magnetic resonance imaging and multivariate data fusion techniques, that is, parallel independent component analysis. RESULTS: The joint analysis of both data modalities explored shared information between GMV and INA. In particular, two amplitudes of low frequency fluctuations-based independent neural systems significantly differed between individuals with SPA and controls. A medial/dorsolateral prefrontal system exhibited lower functional network strength in individuals with SPA versus controls, whereas the opposite pattern was detected in a parietal cortical/cerebellar system. Neural network strength was significantly related to duration of smartphone use and sleep difficulties. DISCUSSION AND CONCLUSIONS: We show modality-specific associations of the brain's resting-state activity with distinct and shared SPA symptom dimensions. In particular, the data suggest contributions of aberrant prefrontal and parietal neural network strength as a possible signature of deficient executive control in SPA. SCIENTIFIC SIGNIFICANCE: This study suggests distinct neural mechanisms underlying specific biological and behavioral dimensions of excessive smartphone use.

The unbalanced behavioral activation and inhibition system sensitivity in internet gaming disorder: Evidence from resting-state Granger causal connectivity analysis.

BACKGROUND: Patients with behavioral or substance addiction show an unbalanced behavioral activation system (BAS) and behavioral inhibition system (BIS) sensitivity. However, the relationship between internet gaming disorder (IGD) and BAS/BIS is obscure and the neurobiological mechanism underlying this relationship remains unclear. METHODS: We recruited 154 IGDs and 229 recreational game users (RGUs) in the current study. First, we explored the relationship between BAS/BIS and IGD. Second, subjects were subdivided into subgroups by BAS/BIS sensitivity. Third, whole-brain Granger causal connectivity (GCC) of striatum and amygdala subdivisions was estimated for the subgroup. Fourth, mediation analysis was performed to explore the role of connectivity in the relationship between IGD and BAS/BIS sensitivity. RESULTS: We found the IGD group scored higher than the RGU on BIS and BASf (fun-seeking) sensitivity. Then, we identified 4 (2*2) subgroups: low/high risk of IGD with low/high BAS/BIS sensitivity groups. Two-way ANCOVA main results of interaction effects showed that in the high BAS/BIS group, the RGU exhibited increased strength in the GCC from the left putamen to the right cuneus, and the IGD exhibited decreased strength in the GCC from the right medial frontal gyrus to the caudate, from the left superior frontal gyrus to the centromedial amygdala, and from the right superior parietal lobule to the left laterobasal amygdala. Moreover, the GCC from the centromedial amygdala to the middle frontal gyrus mediated the directional relationship between BIS and IAT (Young's internet addiction test) scores. CONCLUSIONS: The IGD individuals exhibited higher BIS and BAS-fun seeking sensitivity. Moreover, IGD with unbalanced BAS/BIS sensitivity exhibited alternative connectivity patterns involving amygdala and striatum subdivisions. These findings suggest a neurobiological mechanism for an alternation between IGD and RGU with different BAS/BIS sensitivity.

Gender-related differences in involvement of addiction brain networks in internet gaming disorder: Relationships with craving and emotional regulation.

BACKGROUND: Abnormal interactions among addiction brain networks associated with intoxication, negative affect, and anticipation may have relevance for internet gaming disorder (IGD). Despite prior studies having identified gender-related differences in the neural correlates of IGD, gender-related differences in the involvement of brain networks remain unclear. METHODS: One-hundred-and-nine individuals with IGD (54 males) and 111 with recreational game use (RGU; 58 males) provided resting-state fMRI data. We examined gender-related differences in involvement of addiction brain networks in IGD versus RGU subjects. We further compared the strength between and within addiction brain networks and explored possible relationships between the strength of functional connectivities within and between addiction brain networks and several relevant behavioral measures. RESULTS: The addiction brain networks showed high correct classification rates in distinguishing IGD and RGU subjects in men and women. Male subjects with versus without IGD showed stronger functional connectivities between and within addiction brain networks. Moreover, the strength of the connectivity within the anticipation network in male IGD subjects was positively related to subjective craving. However, female subjects with versus without IGD showed decreased functional connections between and within addiction brain networks. The strength of connectivity between the anticipation and negative-affect brain networks in female IGD subjects was negatively related to maladaptive cognitive emotion-regulation strategies. CONCLUSIONS: Addiction brain networks have potential for distinguishing IGD and RGU individuals. Importantly, this study identified novel gender-related differences in brain-behavior relationships in IGD. These results help advance current neuroscientific theories of IGD and may inform gender-informed treatment strategies.

Enhanced resting-state EEG source functional connectivity within the default mode and reward-salience networks in internet gaming disorder.

BACKGROUND: The two key mechanisms affected by internet gaming disorder (IGD) are cognitive and reward processing. Despite their significance, little is known about neurophysiological features as determined using resting-state electroencephalography (EEG) source functional connectivity (FC). METHODS: We compared resting-state EEG source FC within the default mode network (DMN) and reward/salience network (RSN) between patients with IGD and healthy controls (HCs) to identify neurophysiological markers associated with cognitive and reward processing. A total of 158 young male adults (79 patients with IGD and 79 HCs) were included, and the source FC of the DMN and RSN in five spectral bands (delta, theta, alpha, beta, and gamma) were assessed. RESULTS: Patients with IGD showed increased theta, alpha, and beta connectivity within the DMN between the orbitofrontal cortex and parietal regions compared with HCs. In terms of RSN, patients with IGD exhibited elevated alpha and beta connectivity between the anterior cingulate gyrus and temporal regions compared with HCs. Furthermore, patients with IGD showed negative correlations between the severity of IGD symptoms and/or weekly gaming time and theta and alpha connectivity within the DMN and theta, alpha, and beta connectivity within the RSN. However, the duration of IGD was not associated with EEG source FC. CONCLUSIONS: Hyper-connectivities within the DMN and RSN may be considered potential state markers associated with symptom severity and gaming time in IGD.

Brain functional connectivity during and after imagery of gaming and alternative leisure activities in patients with internet gaming disorder.

BACKGROUND: The effect of gaming cue exposure on brain activity in patients with internet gaming disorder (IGD) has been investigated a lot, but the effect on brain connectivity has not. This study aimed to investigate the effects of imageries of gaming and alternative leisure activities on functional connectivity during the during-task and post-task states in patients with IGD. METHODS: Twenty-nine patients and 20 healthy controls were scanned in the 6-min states before, during, and after the imagery tasks for gaming and alternative leisure behaviors using fMRI. Seed-based functional connectivity during and after the tasks were analyzed. The seeds were the nucleus accumbens (NAcc), ventral tegmental area (VTA), caudate, putamen, anterior cingulate cortex (ACC), and posterior cingulate cortex. RESULTS: The group-by-state interaction effects for the during-tasks were found in caudate-, putamen-, and ACC-based connectivity, whereas those for the post-tasks were shown only in NAcc-based connectivity. In particular, patients showed that caudate-right parahippocampal gyrus connectivity and putamen-right orbitofrontal cortex connectivity increased during gaming and decreased during alternative, whereas NAcc-right precuneus connectivity decreased at baseline, increased in post-gaming, and were not different in post-alternative. CONCLUSION: Differences in during-task connectivity of the habit/motor and salience networks and post-task resting-state connectivity of the reward and limbic networks between the two imagery tasks may differ between the groups. In the treatment of IGD, when these network connections are reactive to alternative leisure activity, just as to gaming activity, they seem to be freed from gaming addiction.

Blunted reward prediction error signals in internet gaming disorder.

BACKGROUND: Internet gaming disorder (IGD) is a type of behavioural addictions. One of the key features of addiction is the excessive exposure to addictive objectives (e.g. drugs) reduces the sensitivity of the brain reward system to daily rewards (e.g. money). This is thought to be mediated via the signals expressed as dopaminergic reward prediction error (RPE). Emerging evidence highlights blunted RPE signals in drug addictions. However, no study has examined whether IGD also involves alterations in RPE signals that are observed in other types of addictions. METHODS: To fill this gap, we used functional magnetic resonance imaging data from 45 IGD and 42 healthy controls (HCs) during a reward-related prediction-error task and utilised a psychophysiological interaction (PPI) analysis to characterise the underlying neural correlates of RPE and related functional connectivity. RESULTS: Relative to HCs, IGD individuals showed impaired reinforcement learning, blunted RPE signals in multiple regions of the brain reward system, including the right caudate, left orbitofrontal cortex (OFC), and right dorsolateral prefrontal cortex (DLPFC). Moreover, the PPI analysis revealed a pattern of hyperconnectivity between the right caudate, right putamen, bilateral DLPFC, and right dorsal anterior cingulate cortex (dACC) in the IGD group. Finally, linear regression suggested that the connection between the right DLPFC and right dACC could significantly predict the variation of RPE signals in the left OFC. CONCLUSIONS: These results highlight disrupted RPE signalling and hyperconnectivity between regions of the brain reward system in IGD. Reinforcement learning deficits may be crucial underlying characteristics of IGD pathophysiology.