The correlation between mood states and functional connectivity within the default mode network can differentiate Internet gaming disorder from healthy controls

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.

Multimodal-based machine learning approach to classify features of internet gaming disorder and alcohol use disorder: A sensor-level and source-level resting-state electroencephalography activity and neuropsychological study

OBJECTIVES

Addictions have recently been classified as substance use disorder (SUD) and behavioral addiction (BA), but the concept of BA is still debatable. Therefore, it is necessary to conduct further neuroscientific research to understand the mechanisms of BA to the same extent as SUD. The present study used machine learning (ML) algorithms to investigate the neuropsychological and neurophysiological aspects of addictions in individuals with internet gaming disorder (IGD) and alcohol use disorder (AUD).

METHODS

We developed three models for distinguishing individuals with IGD from those with AUD, individuals with IGD from healthy controls (HCs), and individuals with AUD from HCs using ML algorithms, including L1-norm support vector machine, random forest, and L1-norm logistic regression (LR). Three distinct feature sets were used for model training: a unimodal-electroencephalography (EEG) feature set combined with sensor- and source-level feature; a unimodal-neuropsychological feature (NF) set included sex, age, depression, anxiety, impulsivity, and general cognitive function, and a multimodal (EEG + NF) feature set.

RESULTS

The LR model with the multimodal feature set used for the classification of IGD and AUD outperformed the other models (accuracy: 0.712). The important features selected by the model highlighted that the IGD group had differential delta and beta source connectivity between right intrahemispheric regions and distinct sensor-level EEG activities. Among the NFs, sex and age were the important features for good model performance.

CONCLUSIONS

Using ML techniques, we demonstrated the neurophysiological and neuropsychological similarities and differences between IGD (a BA) and AUD (a SUD).

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.

Neural basis underlying the relation between internet addiction tendency and sleep quality: The intrinsic default-mode network connectivity pathways

Internet addiction (IA) tendency is considered an addictive behavior that results from excessive Internet use, and severely affecting an individual's physical health, emotion, and sleep. Although previous studies indicated that IA tendency was negatively correlated with sleep quality, the underlying neural basis of this relationship remained unclear. To address this issue, we utilized resting-state functional connectivity (RSFC) analysis to identify the neural pathways of the relationship between IA tendency and sleep quality. The behavioral results indicated a positive correlation between these two factors. And RSFC results revealed that IA tendency was positively related to the strength of functional connectivity within the default-mode network (DMN), including the right precuneus-left middle temporal gyrus (rPrcu-lMTG), the left anterior cingulate-left superior frontal gyrus (lAC-lSFG), and the left inferior parietal lobe-left medial superior frontal gyrus (lIPL-lMSFG). More importantly, mediation analysis demonstrated that IA tendency could mediate the relationship between these functional couplings and sleep quality. In conclusion, our findings suggest that intrinsic DMN connectivity may be an important neural pathways underlying the effects of IA tendency on sleep quality, and provide neural evidence for understanding the relationship between IA tendency and sleep quality.

Methadone maintenance treatment alters couplings of default mode and salience networks in individuals with heroin use disorder: A longitudinal self-controlled resting-state fMRI study

Background

Methadone maintenance treatment (MMT) is a common treatment for heroin use disorder (HUD). Although individuals with HUD have been reported to show impaired coupling among the salience network (SN), executive control network (ECN), and default mode network (DMN), the effects of MMT on the coupling among three large-scale networks in individuals with HUD remains unclear.

Methods

Thirty-seven individuals with HUD undergoing MMT and 57 healthy controls were recruited. The longitudinal one-year follow-up study aimed to evaluate the effects of methadone on anxiety, depression, withdrawal symptoms and craving and number of relapse, and brain function (SN, DMN and bilateral ECN) in relation to heroin dependence. The changes in psychological characteristics and the coupling among large-scale networks after 1 year of MMT were analyzed. The associations between the changes in coupling among large-scale networks and psychological characteristics and the methadone dose were also examined.

Results

After 1 year of MMT, individuals with HUD showed a reduction in the withdrawal symptom score. The number of relapses was negatively correlated with the methadone dose over 1 year. The functional connectivity between the medial prefrontal cortex (mPFC) and the left middle temporal gyrus (MTG; both key nodes of the DMN) was increased, and the connectivities between the mPFC and the anterior insular and middle frontal gyrus (key nodes of the SN) were also increased. The mPFC-left MTG connectivity was negatively correlated with the withdrawal symptom score.

Conclusion

Long-term MMT enhanced the connectivity within the DMN which might be related to reduced withdrawal symptoms, and that between the DMN and SN which might be related to increase in salience values of heroin cues in individuals with HUD. Long-term MMT may be a double-edged sword in treatment for HUD.

Independent component analysis for internet gaming disorder

Introduction: There is a growing interest in the study of the neurobiological correlates of internet gaming disorder (IGD), and new techniques are beginning to be implemented for this purpose, such as independent component analysis (ICA). Aims: The present narrative review aimed to explore the studies that had used ICA for the study of the different brain networks possibly associated with IGD. Methods: We specifically focussed on three of the main networks: default-mode network, executive-control and salience networks. Results: Most studies have identified alterations in these three brain networks in individuals with IGD, which may be involved in the development and maintenance of this disorder. Conclusion: More studies are needed to deepen an understanding of the specific role of each in the symptomatology and treatment of IGD.

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.

Structural and functional brain networks of individual differences in trait anger and anger control: An unsupervised machine learning study

The ability to experience, use and eventually control anger is crucial to maintain well-being and build healthy relationships. Despite its relevance, the neural mechanisms behind individual differences in experiencing and controlling anger are poorly understood. To elucidate these points, we employed an unsupervised machine learning approach based on independent component analysis to test the hypothesis that specific functional and structural networks are associated with individual differences in trait anger and anger control. Structural and functional resting state images of 71 subjects as well as their scores from the State-Trait Anger Expression Inventory entered the analyses. At a structural level, the concentration of grey matter in a network including ventromedial temporal areas, posterior cingulate, fusiform gyrus and cerebellum was associated with trait anger. The higher the concentration, the higher the proneness to experience anger in daily life due to the greater tendency to orient attention towards aversive events and interpret them with higher hostility. At a functional level, the activity of the default mode network (DMN) was associated with anger control. The higher the DMN temporal frequency, the stronger the exerted control over anger, thus extending previous evidence on the role of the DMN in regulating cognitive and emotional functions in the domain of anger. Taken together, these results show, for the first time, two specialized brain networks for encoding individual differences in trait anger and anger control.

Connectome-based prediction of craving for gaming in internet gaming disorder

BACKGROUND

Craving-related brain responses have been associated with the emergence and maintenance of addictions. However, little is known about brain network organizations underlying cravings in internet gaming disorder (IGD).

METHODS

Sixty-six IGD subjects and 61 matched individuals with recreational game use (RGU) were scanned while performing a cue-craving task. A recently developed whole-brain analysis approach, connectome-based predictive modelling (CPM) with leave-one-out cross-validation was conducted to identify networks that predicted craving responses in IGD. Then, the craving network was tested in different brain states (cue-craving under deprivation) to investigate replicability.

RESULTS

CPM identified an IGD craving network, as indicated by a significant correspondence between predicted and actual craving values (r = 0.49, p < 0.001), characterized by within-network default mode (DMN) connectivity and connectivity between canonical networks implicated in executive/cognitive control (frontoparietal, medial frontal, DMN) and reward responsiveness (subcortical, motor/sensory). Network strength in the cue-craving task during gaming deprivation also predicted IGD craving scores (r = 0.43, p = 0.017), indicating network replication across brain states.

CONCLUSIONS

The CPM results demonstrate that individual differences in cognitive, attention, and control network function can predict craving intensities in IGD subjects. These networks may be targets for potential interventions using brain modulation.

Network-wise surface-based morphometric insight into the cortical neural circuitry underlying irritability in adolescents

Previous studies examining structural brain correlates of irritability have taken a region-specific approach and have been relatively inconsistent. In a sample of adolescents with and without clinically impairing irritability, the current study examines: (i) cortical volume (CV) in canonical functional networks; (ii) the association between the CV of functional networks and severity of irritability; and (iii) the extent to which IQ mediates the association between structural abnormalities and severity of irritability. Structural MRI and IQ data were collected from 130 adolescents with high irritability (mean age = 15.54±1.83 years, 58 females, self-reported Affective Reactivity Index [ARI] ≥ 4) and 119 adolescents with low irritability (mean age = 15.10±1.93 years, 39 females, self-reported ARI < 4). Subject-specific network-wise CV was estimated after parcellating the whole brain into 17 previously reported functional networks. Our Multivariate Analysis of Covariance (MANCOVA) revealed that adolescents with high irritability had significantly reduced CV of the bilateral control and default-mode networks (p < 0.05) relative to adolescents with low irritability. Multiple regression analyses showed a significant negative association between the control network CV and the severity of irritability. Mediation analysis showed that IQ partially mediated the association between the control network CV and the severity of irritability. Follow-up analysis on subcortical volume (SCV) showed that adolescents with high irritability had reduced bilateral SCV within the amygdala relative to adolescents with low irritability. Reduced CV within bilateral control and default networks and reduced SCV within bilateral amygdala may represent core features of the pathophysiology of irritability. The current data also indicate the potential importance of a patient's IQ in determining how pathophysiology related to the control network is expressed.

Large-scale network dysfunction in youths with Internet gaming disorder: a meta-analysis of resting-state functional connectivity studies

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.

Resting-state connectome-based support-vector-machine predictive modeling of internet gaming disorder

Internet gaming disorder (IGD), a worldwide mental health issue, has been widely studied using neuroimaging techniques during the last decade. Although dysfunctions in resting-state functional connectivity have been reported in IGD, mapping relationships from abnormal connectivity patterns to behavioral measures have not been fully investigated. Connectome-based predictive modeling (CPM)-a recently developed machine-learning approach-has been used to examine potential neural mechanisms in addictions and other psychiatric disorders. To identify the resting-state connections associated with IGD, we modified the CPM approach by replacing its core learning algorithm with a support vector machine. Resting-state functional magnetic resonance imaging (fMRI) data were acquired in 72 individuals with IGD and 41 healthy comparison participants. The modified CPM was conducted with respect to classification and regression. A comparison of whole-brain and network-based analyses showed that the default-mode network (DMN) is the most informative network in predicting IGD both in classification (individual identification accuracy = 78.76%) and regression (correspondence between predicted and actual psychometric scale score: r = 0.44, P < 0.001). To facilitate the characterization of the aberrant resting-state activity in the DMN, the identified networks have been mapped into a three-subsystem division of the DMN. Results suggest that individual differences in DMN function at rest could advance our understanding of IGD and variability in disorder etiology and intervention outcomes.

Internet gaming disorder impacts gray matter structural covariance organization in the default mode network

INTRODUCTION

Although previous studies have revealed that dysfunctional brain organization is associated with internet gamingdisorder (IGD), the neuroanatomical basis that underlies IGD remains elusive. In this work, we aimed to investigate gray matter (GM) volume alterations and structural covariance patterns in relation to IGD severity.

METHODS

Structural magnetic resonance imaging data were acquired from two hundred and thirty young adults encompassing a wide range of IGD severity. Voxel-based morphometry (VBM) analysis was applied to examine GM volume changes associated with IGD severity. Furthermore, the organization of whole-brain structural covariance network (SCN) was analyzed using the regions identified as seeds from VBM analysis.

RESULTS

Individuals with greater IGD severity had increased GM volumes in the midline components of the default mode network (DMN), namely, the right medial prefrontal cortex (mPFC) and precuneus. More importantly, the SCN results revealed impaired patterns of structural covariance between the DMN-related regions and areas associated with visuospatial attention and reward craving processing as the addiction severity of IGD worsened.

LIMITATIONS

Only young Chinese adults were enrolled in our study andthe extent to which findings generalize to samples in other age groups and diverse cultures is unclear.

CONCLUSIONS

These results showed volume expansion of the DMN components and its weakened structural association with visuospatial attention and motivational craving regions with increasing IGD severity. This study deepens our understanding of the underlying neuroanatomical correlates of IGD, which may help to explain why some individuals are more vulnerable to compulsive gaming usage than others.

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.

Effects of early ketamine exposure on cerebral gray matter volume and functional connectivity

Ketamine has been used for medical purposes, most typically as an anesthetic, and recent studies support its use in the treatment of depression. However, ketamine tends to be abused by adolescents and young adults. In the current study, we examined the effects of early ketamine exposure on brain structure and function. We employed MRI to assess the effects of ketamine abuse on cerebral gray matter volume (GMV) and functional connectivity (FC) in 34 users and 19 non-users, employing covariates. Ketamine users were categorized as adolescent-onset and adult-onset based on when they were first exposed to ketamine. Imaging data were processed by published routines in SPM and AFNI. The results revealed lower GMV in the left precuneus in ketamine users, with a larger decrease in the adolescent-onset group. The results from a seed-based correlation analysis show that both ketamine groups had higher functional connectivity between left precuneus (seed) and right precuneus than the control group. Compared to controls, ketamine users showed decreased GMV in the right insula, left inferior parietal lobule, left dorsolateral prefrontal cortex/superior frontal gyrus, and left medial orbitofrontal cortex. These preliminary results characterize the effects of ketamine misuse on brain structure and function and highlight the influence of earlier exposure to ketamine on the development of the brain. The precuneus, a structure of central importance to cerebral functional organization, may be particularly vulnerable to the influences of early ketamine exposure. How these structural and functional brain changes may relate to the cognitive and affective deficits remains to be determined with a large cohort of participants.

Neurobiological influence of comorbid conditions in young patients diagnosed with gaming disorder: A whole-brain functional connectivity study based on a data driven method

Gaming disorder, which is characterized by multiple cognitive and behavioral symptoms, often has comorbid psychiatric conditions such as depression and attention-deficit hyperactivity disorder. Neurobiological effects of the comorbid disorders so far reported are not converging, exhibiting positive and negative alterations of the connectivity in brain networks. In this study, we conducted resting-state functional magnetic-resonance imaging and whole brain functional connectivity analyses for young participants consisting of 40 patients diagnosed with the gaming disorder, with and without comorbid conditions, and 29 healthy controls. Compared to healthy controls, the gaming disorder-alone patients had partially diminished connectivities in the reward system and executive control network, within which there existed central nodes that served as a hub of diminished connections. In the gaming disorder patients who had comorbidity of autism spectrum disorder, the diminished connections were enlarged, with alteration of the hub nodes, to the entire brain areas involved in the reward system including cortical, subcortical and limbic areas that are crucial for reward processing, and to the whole cortical areas composing the executive control network. These observations suggest that the neurodevelopmental condition coexisting with the gaming disorder induced substantial impairment of the neural organizations associated with executive/cognitive and emotional functions, which are plausibly causal to the behavioral addiction, by rearranging and diminishing functional connectivities in the network.

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

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.

Sex differences in resting-state cerebral activity alterations in internet gaming disorder

Although evidence has shown that the prevalence rates of Internet gaming disorder (IGD) differ between males and females, few studies have examined whether such sex differences extend to brain function. This study aimed to explore the sex differences in resting-state cerebral activity alterations in IGD. Thirty male participants with IGD (IGDm), 23 female participants with IGD (IGDf), and 30 male and 22 female age-matched healthy controls (HC) underwent resting-state functional MRI. Maps of the amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) were constructed. A two-factor ANCOVA model was performed, with sex and diagnosis as the between-subject factors. Then, post hoc pair-wise comparisons were performed using two-sample t-tests within the interaction masks. The Barratt Impulsiveness Scale-11 (BIS-11) was used to assess the behavioral inhibition function. We found that the ALFF values in the orbital part of the left superior frontal gyrus (SFG) were lower in IGDm than in HCm, which were negatively correlated with BIS-11 scores. IGDm also demonstrated lower connectivity between the orbital part of the left SFG and the posterior cingulate cortex (PCC), the right angular gyrus, and the right dorsolateral prefrontal cortex than HCm. Furthermore, IGDm had lower seed connectivity between the orbital part of the left SFG and the PCC than ICDf. Our findings suggest that (1) the altered ALFF values in the orbital part of the left SFG represent a clinically relevant biomarker for the behavioral inhibition function of IGDm; (2) IGD may interact with sex-specific patterns of FC in male and female subjects.

Internet addiction and functional brain networks: task-related fMRI study

A common brain-related feature of addictions is the altered function of higher-order brain networks. Growing evidence suggests that Internet-related addictions are also associated with breakdown of functional brain networks. Taking into consideration the limited number of studies used in previous studies in Internet addiction (IA), our aim was to investigate the functional correlates of IA in the default mode network (DMN) and in the inhibitory control network (ICN). To observe these relationships, task-related fMRI responses to verbal Stroop and non-verbal Stroop-like tasks were measured in 60 healthy university students. The Problematic Internet Use Questionnaire (PIUQ) was used to assess IA. We found significant deactivations in areas related to the DMN (precuneus, posterior cingulate gyrus) and these areas were negatively correlated with PIUQ during incongruent stimuli. In Stroop task the incongruent_minus_congruent contrast showed positive correlation with PIUQ in areas related to the ICN (left inferior frontal gyrus, left frontal pole, left central opercular, left frontal opercular, left frontal orbital and left insular cortex). Altered DMN might explain some comorbid symptoms and might predict treatment outcomes, while altered ICN may be the reason for having difficulties in stopping and controlling overuse.

Meta-analyses of the functional neural alterations in subjects with Internet gaming disorder: Similarities and differences across different paradigms

Internet gaming disorder (IGD) has become a global public health concern due to its increasing prevalence and potential negative consequences. Researchers have sought to identify which brain regions are associated with this disorder. However, inconsistent results have been reported among studies due to the heterogeneity of paradigms and subjects. The present research aimed to combine the results of individual studies to provide a more coherent and powerful explanation. By selecting 40 studies utilizing a qualified whole-brain analysis, we performed a comprehensive series of meta-analyses that employed seed-based d mapping. We divided the existing experimental paradigms into 3 categories: game-related cue-reactivity, executive control, and risk-reward-related decision-making tasks. We divided all studies into three subgroups according to their paradigms. In cue-reactivity tasks, patients with IGD exhibited significant hyperactivation in the bilateral precuneus and bilateral cingulate and significant hypoactivation in the insula, but there were no differences in the striatum. In executive control tasks, patients with IGD displayed significant hyperactivation in the right superior temporal gyrus, bilateral precuneus, bilateral cingulate, and insula and hypoactivation in the left inferior frontal gyrus. In risky decision-making paradigms, IGD patients exhibited significant hyperactivation in the left striatum, right inferior frontal gyrus, and insula and hypoactivation in the left superior frontal gyrus, left inferior frontal gyrus, and right precentral gyrus. Our study aimed to discover the similarities among all studies and to explore the uniqueness of the different paradigms. This study further confirmed the critical role of reward circuitry and executive control circuitry in IGD but not under all conditions.

The Mediating Effects of Affect on Associations between Impulsivity or Resilience and Internet Gaming Disorder

Internet gaming disorder (IGD) is a new disease proposed by the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5), and has been studied extensively in relation to depression and impulsivity. The relationship between resilience and disease has been found in a variety of addictive disorders, but studies on IGD are lacking. In this study, 71 IGD patients and 78 healthy controls (HCs) were recruited. Impulsivity, resilience, affects, and the degree of internet game addiction were measured using formal tools. The measured values were analyzed by mediation analysis to evaluate the mediating role of affects on resilience and impulsivity related to IGD symptoms. The IGD group showed higher impulsivity, lower resilience, lower positive affect, and higher negative affect than the HC group. The mediation analysis showed that a positive affect was a mediator between impulsivity and the severity of addiction in both groups. Negative affect mediated impulsivity/resilience and the severity of addiction only in the IGD group. Although the results of this study are based on a narrow category of subjects, who are young male adults around 25 years of age, the results suggest that positive affect can be strengthened to prevent the IGD illness, and that illness symptoms may be alleviated by reducing negative affect.

Mapping Internet gaming disorder using effective connectivity: A spectral dynamic causal modeling study

OBJECTS

Understanding the neural basis underlying Internet gaming disorder (IGD) is essential for the diagnosis and treatment of this type of behavioural addiction. Aberrant resting-state functional connectivity (rsFC) of the default mode network (DMN) has been reported in individuals with IGD. Since rsFC is not a directional analysis, the effective connectivity within the DMN in IGD remains unclear. Here, we employed spectral dynamic causal modeling (spDCM) to explore this issue.

METHODS

Resting state fMRI data were collected from 64 IGD (age: 22.6 ± 2.2) and 63 well-matched recreational Internet game users (RGU, age: 23.1 ± 2.5). Voxel-based mean time series data extracted from the 4 brain regions within the DMN (medial prefrontal cortex, mPFC; posterior cingulate cortex, PCC; bilateral inferior parietal lobule, left IPL/right IPL) of two groups during the resting state were used for the spDCM analysis.

RESULTS

Compared with RGU, IGD showed reduced effective connectivity from the mPFC to the PCC and from the left IPL to the mPFC, with reduced self-connection in the PCC and the left IPL.

CONCLUSIONS

The spDCM could distinguish the changes in the functional architecture between two groups more precisely than rsFC. Our findings suggest that the decreased excitatory connectivity from the mPFC to the PCC may be a crucial biomarker for IGD. Future brain-based intervention should pay attention to dysregulation in the IPL-mPFC-PCC circuits.

Association of Fatigue and Stress With Gray Matter Volume

Stress is associated with a greater risk for various health problems including reduced gray matter volume (GMV) and density in a number of brain regions. Previous studies show that neuroimaging could be a means to objectively evaluate stress. However, to date, no definite neuroimaging-derived measures are available to detect stress. In this research we used the gray-matter brain healthcare quotient (GM-BHQ), an MRI-based quotient for monitoring brain health based on GMV, as an objective scale to measure the association of stress with the whole brain. We recruited 63 healthy adults to acquire structural T1-weighted images and stress levels evaluated using three representative stress scales: the Profile of Mood States (POMS), Perceived Stress Scale (PSS) and Chalder Fatigue Scale (CFS). We found that the GM-BHQ was sensitive to fatigue and the interaction between fatigue and stress.