Decreased effective connection from the parahippocampal gyrus to the prefrontal cortex in Internet gaming disorder: A MVPA and spDCM study

Efficacy and neural mechanisms of approach bias modification training in patients with internet gaming disorder: A randomized clinical trial

BACKGROUND

Internet gaming disorder (IGD) is a prevalent behavioral addiction linked to neural alterations and significant negative outcomes. Approach bias modification (ApBM) training aims to correct imbalances in reflective and impulsive systems, reducing cravings and addictions. This study examined the effectiveness of ApBM training in IGD patients and explored the brain response changes associated with the intervention.

METHODS

Fifty-one patients with IGD were randomly assigned to an ApBM group (n = 26) or a sham-ApBM group (n = 25). Resting-state functional magnetic resonance imaging scans and behavioral assessments, including Internet Addiction Test scores, DSM-5 criteria, game craving levels, and automatic approach bias, were conducted before and after a ten-day training with five sessions. An analysis of variance (ANOVA) was employed to assess time (pre- and post-test) × group (ApBM group vs. sham-ApBM group) effects on behavioral measures. Functional connectivity (FC) analyses focused on regions of interest identified through regional homogeneity and degree centrality calculations. Additionally, we analyzed the relationship between neuroimaging variables and intervention outcomes.

RESULTS

Significant group × time interactions were found for automatic approach bias, Internet Addiction Test scores, DSM-5 criteria, and game craving levels. Post-training, these measures significantly decreased in the ApBM group but showed no significant changes in the sham-ApBM group. FC analysis revealed increased connectivity within executive control regions, enhanced connectivity between executive control and reward-related regions, and decreased connectivity within reward-related regions, exclusively in the ApBM group.

CONCLUSIONS

ApBM training effectively reduces gaming cravings in patients with IGD, enhancing executive control and mitigating impulsive behaviors.

Functional connectome gradient of prefrontal cortex as biomarkers of high risk for internet gaming disorder

Adolescents and young adults are considered a high-risk group for internet gaming disorder (IGD). Early screening for high-risk individuals with IGD and exploring the underlying neural mechanisms is an effective strategy to reduce the harm of IGD. We recruited 219 non-internet gaming addicted college students and evaluated them with magnetic resonance imaging, followed by a two-year longitudinal follow-up. We used functional connectome gradient (FCG) to capture the macroscopic hierarchical organization of human brain. Canonical correlation analysis was employed to identify components mapping relationships between FCG and behavioral scores. Consequently, K-means clustering was used to define distinct subtypes. The risk of developing IGD and FCG patterns were compared among the subtypes. Three subtypes were identified and subtype 3 exhibited the highest risk for developing IGD according to the occurrence rates of IGD two years later: (1) subtype 1 (5.3 %, 4 participants), (2) subtype 2 (10.8 %, 9 participants), (3) subtype 3 (20 %, 12 participants). The abnormal FCG in the inferior frontal gyrus and posterior cingulate cortex at baseline were observed in subtype 3, which were correlated with impulsivity. These findings advanced understanding of the biological and behavioral heterogeneity associated with developing of IGD, and represented a promising step toward the prediction of high-risk individuals.

Deep brain stimulation of the anterior cingulate cortex reduces opioid addiction in preclinical studies

Substance Use Disorder (SUD) is a medical condition where an individual compulsively misuses drugs or alcohol despite knowing the negative consequences. The anterior cingulate cortex (ACC) has been implicated in various types of SUDs, including nicotine, heroin, and alcohol use disorders. Our research aimed to investigate the effects of deep brain stimulation (DBS) in the ACC as a potential therapeutic approach for morphine use disorder. Additionally, we measured c-Fos protein expression as an indicator of neural activity in the nucleus accumbens (NAc) and prefrontal cortex (PFC). Our findings indicate that high-frequency (130 Hz) DBS at different amperages, 150 µA and 200 µA in the ACC during the acquisition phase of morphine conditioned place preference (CPP) inhibited the rewarding properties of morphine. Furthermore, DBS at these intensities during the extinction phase facilitated the extinction and mitigated the reinstatement of morphine CPP triggered by drug priming. Morphine conditioning was associated with impaired novel object conditioning (NOR) and locomotor activity. While DBS in the acquisition and extinction phases at both intensities restored NOR memory, only DBS at 200 µA recovered locomotor activity in the open field test. Treatment with DBS at 200 µA decreased c-Fos protein expression in the NAc and PFC (compared to morphine-only group). In conclusion, our data indicate an intensity-dependent effect of ACC DBS on the acquisition, extinction, and reinstatement of morphine-induced CPP in rats. These findings suggest that ACC DBS could be a potential intervention for the treatment of morphine use disorder.

Biomarkers of Internet Gaming Disorder-A Narrative Review

Since game mechanics and their visual aspects have become more and more addictive, there is concern about the growing prevalence of Internet gaming disorder (IGD). In the current narrative review, we searched PubMed and Google Scholar databases for the keywords "igd biomarker gaming" and terms related to biomarker modalities. The biomarkers we found are grouped into several categories based on a measurement method and are discussed in the light of theoretical addiction models (tripartite neurocognitive model, I-PACE). Both theories point to gaming-related problems with salience and inhibition. The first dysfunction makes an individual more susceptible to game stimuli (raised reward seeking), and the second negatively impacts resistance to these stimuli (decreased cognitive control). The IGD patients' hypersensitivity to reward manifests mostly in ventral striatum (VS) measurements. However, there is also empirical support for a ventral-to-dorsal striatal shift and transition from goal-directed to habitual behaviors. The deficits in executive control are demonstrated in parameters related to the prefrontal cortex (PFC), especially the dorsolateral prefrontal cortex (DLPFC). In general, the connection of PFC with reward under cortex nuclei seems to be dysregulated. Other biomarkers include reduced P3 amplitudes, high-frequency heart rate variability (HRV), and the number of eye blinks and saccadic eye movements during the non-resting state. A few studies propose a diagnostic (multimodal) model of IGD. The current review also comments on inconsistencies in findings in the nucleus accumbens (NAcc), anterior cingulate cortex (ACC), and precuneus and makes suggestions for future IGD studies.

Mindfulness Meditation Training Reduces Gaming Cravings by Reshaping the Functional Connectivity Between the Default Mode Network and Executive Control-Related Brain Regions

BACKGROUND

Internet gaming disorder (IGD) can lead to psychological problems and cause behavioral problems in individuals. Traditional interventions have been ineffective in treating IGD. Meanwhile, mindfulness meditation (MM) is an emerging method that has proven to be effective for treating psychiatric disorders. In this study, MM was used to intervene in IGD and to explore its neural mechanism.

METHODS

Eighty participants were recruited through advertisements. Eventually, 61 completed the 1-month training (MM group, n = 31; progressive muscle relaxation [PMR] group, n = 30), including a pretest, 8 training sessions, and a posttest. Regional homogeneity and degree centrality were calculated, and the tests (pre- and post-) and group (MM and PMR) analysis of variance was performed. The overlapping results were obtained as region of interest for functional connectivity (FC) analyses. Behavioral data and neurotransmitter availability maps were correlated with FC.

RESULTS

Compared with PMR, MM decreased the severity of addiction and game craving in IGD. Brain imaging results showed that the FC between and within the executive control and default mode networks/reward-related regions were enhanced. Significant negative correlations were observed between FC and dopamine receptor D2, dopamine transporter, and vesicular acetylcholine transporter. Significant positive correlations were observed between FCs and serotonin and aminobutyric acid receptors.

CONCLUSIONS

This study confirmed the effectiveness of MM in treating IGD. MM altered the default mode and enhanced top-down control over game cravings. These findings were revealed by the correlations between brain regions and behavioral and biochemical effects. The results show the neural mechanism of MM in reducing IGD and lay the foundation for future research.

Sex differences of neural connectivity in internet gaming disorder and its association with sleep quality: an exploratory fMRI study

Objectives

Sex-specific differences in internet gaming disorder (IGD) neurophysiology remain underexplored. Here we investigated sex-related variability in regional homogeneity (ReHo) and functional connectivity (FC) in IGD and their correlations with sleep quality.

Methods

Resting-state functional magnetic resonance imaging (fMRI) scans were performed on 52 subjects with IGD and 50 healthy controls (HCs). Two-way ANOVA was used to examine sex and diagnosis interactions in ReHo and FC, followed by post-hoc analyses to explore FC biomarkers for different sexes.

Results

In ReHo analysis, the four groups showed significant sex and diagnosis interactions in the right middle frontal gyrus (rMFG). FC analysis with rMFG as the seed region revealed a significant sex and diagnosis interaction effect in FC of the rMFG with the bilateral postcentral gyrus (PoCG). In male IGD group, FC between the rMFG and the bilateral PoCG correlates strongly with daytime dysfunction score and the Pittsburgh sleep quality inventory (PSQI) total score.

Conclusion

These findings emphasize the importance of considering sexual dimorphism in the neurobiology of IGD, which might influence subsequent treatment strategies.

Aberrant concordance among dynamics of spontaneous brain activity in patients with migraine without aura: A multivariate pattern analysis study

Background

Alterations in the static and dynamic characteristics of spontaneous brain activity have been extensively studied to investigate functional brain changes in migraine without aura (MwoA). However, alterations in concordance among the dynamics of spontaneous brain activity in MwoA remain largely unknown. This study aimed to determine the possibilities of diagnosis based on the concordance indices.

Methods

Resting-state functional MRI scans were performed on 32 patients with MwoA and 33 matched healthy controls (HCs) in the first cohort, as well as 36 patients with MwoA and 32 HCs in the validation cohort. The dynamic indices including fractional amplitude of low-frequency fluctuation, regional homogeneity, voxel-mirrored homotopic connectivity, degree centrality and global signal connectivity were analyzed. We calculated the concordance of grey matter volume-wise (across voxels) and voxel-wise (across time windows) to quantify the degree of integration among different functional levels represented by these dynamic indices. Subsequently, the voxel-wise concordance alterations were analyzed as features for multi-voxel pattern analysis (MVPA) utilizing the support vector machine.

Results

Compared with that of HCs, patients with MwoA had lower whole-grey matter volume-wise concordance, and the mean value of volume-wise concordance was negatively correlated with the frequency of migraine attacks. The MVPA results revealed that the most discriminative brain regions were the right thalamus, right cerebellar Crus II, left insula, left precentral gyrus, right cuneus, and left inferior occipital gyrus.

Conclusions

Concordance alterations in the dynamics of spontaneous brain activity in brain regions could be an important feature in the identification of patients with MwoA.

Neural Network Dynamics and Brain Oscillations Underlying Aberrant Inhibitory Control in Internet Addiction

Previous studies have reported a role of alterations in the brain's inhibitory control mechanism in addiction. Mounting evidence from neuroimaging studies indicates that its key components can be evaluated with brain oscillations and connectivity during inhibitory control. In this study, we developed an internet-related stop-signal task with electroencephalography (EEG) signal recorded to investigate inhibitory control. Healthy controls and participants with Internet addiction were recruited to participate in the internet-related stop-signal task with 19-channel EEG signal recording, and the corresponding event-related potentials and spectral perturbations were analyzed. Brain effective connections were also evaluated using direct directed transfer function. The results showed that, relative to the healthy controls, participants with Internet addiction had increased Stop-P3 during inhibitory control, suggesting that they have an altered neural mechanism in impulsive control. Furthermore, participants with Internet addiction showed increased low-frequency synchronization and decreased alpha and beta desynchronization in the middle and right frontal regions compared to healthy controls. Aberrant brain effective connectivity was also observed, with increased occipital-parietal and intra-occipital connections, as well as decreased frontal-paracentral connection in participants with Internet addiction. These results suggest that physiological signals are essential in future implementations of cognitive assessment of Internet addiction to further investigate the underlying mechanisms and effective biomarkers.

Association between gaming disorder and regional homogeneity in highly involved male adult gamers: A pilot resting-state fMRI study

BACKGROUND

Gaming behavior can induce cerebral changes that may be related to the neurobiological features of gaming disorder (GD). Additionally, individuals with higher levels of depression or impulsivity are more likely to experience GD. Therefore, the present pilot study explored potential neurobiological correlates of GD in the context of depression and impulsivity, after accounting for video gaming behavior.

METHODS

Using resting-state functional magnetic resonance imaging (fMRI), a cross-sectional study was conducted with 35 highly involved male adult gamers to examine potential associations between GD severity and regional homogeneity (ReHo) in the entire brain. A mediation model was used to test the role of ReHo in the possible links between depression/impulsivity and GD severity.

RESULTS

Individuals with greater GD severity showed increased ReHo in the right Heschl's gyrus and decreased ReHo in the right hippocampus (rHip). Furthermore, depression and impulsivity were negatively correlated with ReHo in the rHip, respectively. More importantly, ReHo in the rHip was found to mediate the associations between depression/impulsivity and GD.

CONCLUSIONS

These preliminary findings suggest that GD severity is related to ReHo in brain regions associated with learning/memory/mood and auditory function. Higher levels of depression or impulsivity may potentiate GD through the functional activity of the hippocampus. Our findings advance our understanding of the neurobiological differences behind GD symptoms in highly involved gamers.

Altered effective connectivity from cerebellum to motor cortex in chronic low back pain: A multivariate pattern analysis and spectral dynamic causal modeling study

To explore the central processing mechanism of pain perception in chronic low back pain (cLBP) using multi-voxel pattern analysis (MVPA) based on the static and dynamic fractional amplitude of low-frequency fluctuations (fALFF) analysis, and spectral dynamic causal modeling (spDCM). Thirty-two patients with cLBP and 29 matched healthy controls (HCs) for the first cohort and 24 patients with cLBP and 22 HCs for the validation cohort underwent resting-state fMRI scan. The alterations in static and dynamic fALFF were as classification features to distinguish patients with cLBP from HCs. The brain regions gotten from the MVPA results were used for further spDCM analysis. We found that the most discriminative brain regions that contributed to the classification were the right supplementary motor area (SMA.R), left paracentral lobule (PCL.L), and bilateral cerebellar Crus II. The spDCM results displayed decreased excitatory influence from the bilateral cerebellar Crus II to PCL.L in patients with cLBP compared with HCs. Moreover, the conversion of effective connectivity from the bilateral cerebellar Crus II to SMA.R from excitatory influence to inhibitive influence, and the effective connectivity strength exhibited partially mediated effects on Chinese Short Form Oswestry Disability Index Questionnaire (C-SFODI) scores. Our findings suggest that the cerebellum and its weakened or inhibited connections to the motor cortex may be one of the underlying feedback pathways for pain perception in cLBP, and partially mediate the degree of dysfunction.

Right inferior frontal gyrus theta-burst stimulation reduces smoking behaviors and strengthens fronto-striatal-limbic resting-state functional connectivity: a randomized crossover trial

Introduction

Functional and anatomical irregularities in the right inferior frontal gyrus (rIFG), a ventrolateral prefrontal region that mediates top-down inhibitory control over prepotent behavioral responding, are implicated in the ongoing maintenance of nicotine dependence (ND). However, there is little research on the effects of neuromodulation of the rIFG on smoking behavior, inhibitory control, and resting-state functional connectivity (rsFC) among individuals with ND.

Methods

In this double-blind, crossover, theta-burst stimulation (TBS) study, adults with ND (N = 31; female: n = 15) completed a baseline session and were then randomized to two counterbalanced sessions of functionally neuronavigated TBS to the rIFG: continuous TBS (cTBS) on 1 day and intermittent TBS (iTBS) on another. Differences in cigarette cravings, smoking, and fronto-striatal-limbic rsFC were assessed.

Results

Relative to baseline, cTBS significantly reduced appetitive and withdrawal cravings immediately after treatment. The effects of cTBS on withdrawal craving persisted for 24 h, as well as produced a reduction in smoking. Furthermore, cTBS significantly strengthened rsFC between the rIFG pars opercularis and subcallosal cingulate (fronto-striatal circuit), and between the rIFG pars opercularis and the right posterior parahippocampal gyrus (fronto-limbic circuit). At post-24 h, cTBS-induced increase in fronto-striatal rsFC was significantly associated with less appetitive craving, while the increase in fronto-limbic rsFC was significantly associated with less withdrawal craving and smoking.

Discussion

These findings warrant further investigation into the potential value of rIFG cTBS to attenuate smoking behavior among individuals with ND.

Adverse childhood experiences, problematic internet use, and health-related quality of life in Chinese adolescents

Background: The influence of adverse childhood experiences (ACEs) on an individual's health is substantial. However, the associations between ACEs, problematic internet use (PIU), and health-related quality of life (HRQOL) in adolescents remain underexplored.Objective: To assess the association between ACEs and HRQOL in Chinese adolescents and to evaluate the mediating role of PIU in this association.Method: A sample of 6,639 adolescents (3,457 boys and 3,182 girls) aged between 11-20 years (mean [SD] age: 14.5 [1.6] years) were recruited from 6 junior and senior middle schools using a proportional sampling approach in a cross-sectional study. Data on ACE exposure was collected through the short form of Childhood Trauma Questionnaire, the ACE-International Questionnaire, and two additional questions. HRQOL was assessed by the Pediatric Quality of Life Inventory version 4.0. The associations between ACEs and HRQOL were estimated using linear regression models. Mediation analysis was further conducted to explore the possible mediating role of PIU in the association between ACEs and HRQOL.Results: Our study collected 13 different ACEs. We found that adolescents exposed to any ACE had significantly lower scores in all HRQOL dimensions, psychosocial health summary scale, and total scale, than those without such exposure. Specifically, adolescents with ≥ 3 ACE exposure had a total scale score that was 14.70 (95%CI: 15.53 to 13.87) points lower than their non-exposed counterparts. Mediation analysis identified PIU as a significant mediator, with the proportion of the total effect attributable to PIU ranging from 14.38% for social functioning to 17.44% for physical functioning.Conclusions: Exposure to ACEs was associated with poorer HRQOL in Chinese adolescents, underscoring the importance to prevent ACEs and their negative impacts on adolescent well-being. These findings also highlighted the need of promoting appropriate internet use among adolescents exposed to ACEs, in order to avert potential impairment in their HRQOL.HIGHLIGHTSAdolescents with adverse childhood experiences have poorer health-related quality of life.The association between adverse childhood experiences and health-related quality of life shows a dose-response pattern.Problematic internet use partially mediates the associations between adverse childhood experiences and health-related quality of life in adolescents.

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.

Altered Brain Structural Reorganization and Hierarchical Integrated Processing in Obesity

The brain receives sensory information about food, evaluates its desirability and value, and responds with approach or withdrawal. The evaluation process of food in the brain with obesity may involve a variety of neurocircuit abnormalities in the integration of internal and external information processing. There is a lack of consistency of the results extant reported for aberrant changes in the brain with obesity that prohibits key brain alterations to be identified. Moreover, most studies focus on the observation of neural plasticity of function or structure, and the evidence for functional and structural correlations in the neuronal plasticity process of obesity is still insufficient. The aims of this article are to explore the key neural structural regions and the hierarchical activity pattern of key structural nodes and evaluate the correlation between changes in functional modulation and eating behavior. Forty-two participants with obesity and 33 normal-weight volunteers were recruited. Gray matter volume (GMV) and Granger causality analysis (GCA) were performed using the DPARSF, CAT12, and DynamicBC toolbox. Compared with the normal weight group, the obesity group exhibited significantly increased GMV in the left parahippocampal gyrus (PG). The obesity group showed decreased causal inflow to the left PG from the left orbitofrontal cortex (OFC), right calcarine, and bilateral supplementary motor area (SMA). Decreased causal outflow to the left OFC, right precuneus, and right SMA from the left PG, as well as increased causal outflow to the left middle occipital gyrus (MOG) were observed in the obesity group. Negative correlations were found between DEBQ-External scores and causal outflow from the left PG to the left OFC, and DEBQ-Restraint scores and causal inflow from the left OFC to the left PG in the obesity group. Positive correlation was found between DEBQ-External scores and causal outflow from the left PG to the left MOG. These results show that the increased GMV in the PG may play an important role in obesity, which may be related to devalued reward system, altered behavioral inhibition, and the disengagement of attentional and visual function for external signals. These findings have important implications for understanding neural mechanisms in obesity and developing individual-tailored strategies for obesity prevention.

Random Network and Non-rich-club Organization Tendency in Children With Non-syndromic Cleft Lip and Palate After Articulation Rehabilitation: A Diffusion Study

Objective

The neuroimaging pattern in brain networks after articulation rehabilitation can be detected using graph theory and multivariate pattern analysis (MVPA). In this study, we hypothesized that the characteristics of the topology pattern of brain structural network in articulation-rehabilitated children with non-syndromic cleft lip and palate (NSCLP) were similar to that in healthy comparisons.

Methods

A total of 28 children with NSCLP and 28 controls with typical development were scanned for diffusion tensor imaging on a 3T MRI scanner. Structural networks were constructed, and their topological properties were obtained. Besides, the Chinese language clear degree scale (CLCDS) scores were used for correlation analysis with topological features in patients with NSCLP.

Results

The NSCLP group showed a similar rich-club connection pattern, but decreased small-world index, normalized rich-club coefficient, and increased connectivity strength of connections compared to controls. The univariate and multivariate patterns of the structural network in articulation-rehabilitated children were primarily in the feeder and local connections, covering sensorimotor, visual, frontoparietal, default mode, salience, and language networks, and orbitofrontal cortex. In addition, the connections that were significantly correlated with the CLCDS scores, as well as the weighted regions for classification, were chiefly distributed in the dorsal and ventral stream associated with the language networks of the non-dominant hemisphere.

Conclusion

The average level rich-club connection pattern and the compensatory of the feeder and local connections mainly covering language networks may be related to the CLCDS in articulation-rehabilitated children with NSCLP. However, the patterns of small-world and rich-club structural organization in the articulation-rehabilitated children exhibited a random network and non-rich-club organization tendency. These findings enhanced the understanding of neuroimaging patterns in children with NSCLP after articulation rehabilitation.

Identifying Internet Addiction and Evaluating the Efficacy of Treatment Based on Functional Connectivity Density: A Machine Learning Study

Although mounting neuroimaging studies have greatly improved our understanding of the neurobiological mechanism underlying internet addiction (IA), the results based on traditional group-level comparisons are insufficient in guiding individual clinical practice directly. Specific neuroimaging biomarkers are urgently needed for IA diagnosis and the evaluation of therapy efficacy. Therefore, this study aimed to develop support vector machine (SVM) models to identify IA and assess the efficacy of cognitive behavior therapy (CBT) based on unbiased functional connectivity density (FCD). Resting-state fMRI data were acquired from 27 individuals with IA before and after 8-week CBT sessions and 30 demographically matched healthy controls (HCs). The discriminative FCDs were computed as the features of the support vector classification (SVC) model to identify individuals with IA from HCs, and the changes in these discriminative FCDs after treatment were further used as features of the support vector regression (SVR) model to evaluate the efficacy of CBT. Based on the informative FCDs, our SVC model successfully differentiated individuals with IA from HCs with an accuracy of 82.5% and an area under the curve (AUC) of 0.91. Our SVR model successfully evaluated the efficacy of CBT using the FCD change ratio with a correlation efficient of 0.59. The brain regions contributing to IA classification and CBT efficacy assessment were the left inferior frontal cortex (IFC), middle frontal cortex (MFC) and angular gyrus (AG), the right premotor cortex (PMC) and middle cingulate cortex (MCC), and the bilateral cerebellum, orbitofrontal cortex (OFC) and superior frontal cortex (SFC). These findings confirmed the FCDs of hyperactive impulsive habit system, hypoactive reflecting system and sensitive interoceptive reward awareness system as potential neuroimaging biomarkers for IA, which might provide objective indexes for the diagnosis and efficacy evaluation of IA.

Altered modular segregation of brain networks during the cue-craving task contributes to the disrupted executive functions in internet gaming disorder

BACKGROUND

Previous studies have shown that gaming-related cues could induce gaming cravings and bring about changes in brain activities in subjects with Internet gaming disorder (IGD). However, little is known about the brain network organizations in IGD subjects during a cue-craving task and the relationship between this network organization and IGD severity.

METHODS

Sixty-one IGD subjects and 61 matched recreational game users (RGUs) were scanned while performing a cue-craving task. We calculated and compared the participation coefficient (PC) among brain network modules between IGD subjects and RGUs. Based on the results, further group comparison analyses were performed to explain the PC changes and to explore the relationship between PCs and IGD severity.

RESULTS

While performing a cue-craving task, compared with RGUs, IGD subjects showed significantly decreased PCs in the default-mode network (DMN) and the frontal-parietal network (FPN). Specifically, the number of connections between nodes in the ventromedial prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex and other nodes in the DMN of IGD subjects was much larger than that in RGUs. Correlation results showed that the number of DMN intra-modular connections was positively correlated with addiction severity and craving degree.

CONCLUSIONS

These results provide neural evidence that can explain why cognitive control, emotion, attention and other functions are impaired in IGD subjects in the face of gaming cues, which leads to compulsive behavior toward games. These findings extend our understanding of the neural mechanism of IGD and have important implications for developing effective interventions to treat IGD subjects.

More stringent criteria are needed for diagnosing internet gaming disorder: Evidence from regional brain features and whole-brain functional connectivity multivariate pattern analyses

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.

More stringent criteria are needed for diagnosing internet gaming disorder: Evidence from regional brain features and whole-brain functional connectivity multivariate pattern analyses

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.