Efficacy and Neural Mechanisms of Mindfulness Meditation Among Adults With Internet Gaming Disorder: A Randomized Clinical Trial.

Importance: The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR), recently identified internet gaming disorder (IGD) as a condition warranting more research, and few empirically validated treatments exist. Mindfulness meditation (MM) has multiple health benefits; however, its efficacy in treating IGD and potential neural mechanisms underlying MM treatment of the disorder remain largely unknown. Objective: To explore the efficacy of MM used to treat adults with IGD and to identify neural mechanisms underlying MM. Design, Setting, and Participants: This randomized clinical trial was performed from October 1 to November 30, 2023, at Hangzhou Normal University in Hangzhou, China. Adults (aged ≥18 years) who met at least 6 of the 9 DSM-5-TR proposed criteria for IGD were recruited to receive either MM or progressive muscle relaxation (PMR). Data analysis was performed on December 1, 2023. Intervention: Participants underwent MM training (an 8-session meditation program that focuses on attention and acceptance) and PMR training (an 8-time program for body relaxation) delivered in groups that met 2 times each week for 4 weeks. Main Outcomes and Measures: This per-protocol analysis included only participants who finished the pretest assessment, 8 training sessions, and posttest assessment. The main outcomes were addiction severity (measured with the DSM-5-TR proposed criteria for IGD and with Internet Addiction Test scores), gaming craving (measured with Questionnaire for Gaming Urges scores), and blood oxygen level-dependent signals assessed with cue-craving tasks on fMRI. Behavioral and brain measurements were compared using analysis of variance. Functional connectivity (FC) among identified brain regions was measured to test connectivity changes associated with MM. Results: This study included 64 adults with IGD. A total of 32 participants received MM (mean [SD] age, 20.3 [1.9] years; 17 women [53%]) and 32 received PMR (mean [SD] age, 20.2 [1.5] years; 16 women [50%]). The severity of IGD decreased in the MM group (pretest vs posttest: mean [SD], 7.0 [1.1] vs 3.6 [0.8]; P < .001) and in the PMR group (mean [SD], 7.1 [0.9] vs 6.0 [0.9]; P = .04). The MM group had a greater decrease in IGD severity than the PMR group (mean [SD] score change for the MM group vs the PMR group, -3.6 [0.3] vs -1.1 [0.2]; P < .001). Mindfulness meditation was associated with decreased brain activation in the bilateral lentiform nuclei (r = 0.40; 95% CI, 0.19 to 0.60; P = .02), insula (r = 0.35; 95% CI, 0.09 to 0.60; P = .047), and medial frontal gyrus (MFG; r = 0.43; 95% CI, 0.16 to 0.70; P = .01). Increased MFG-lentiform FC and decreased craving (pretest vs posttest: mean [SD], 58.8 [15.7] vs 33.6 [12.0]; t = -8.66; ƞ2 = 0.30; P < .001) was observed after MM, and changes in MFG-lentiform FC mediated the relationship between increased mindfulness and decreased craving (mediate effect, -0.17; 95% CI, -0.32 to -0.08; P = .03). Conclusions and Relevance: In this study, MM was more effective in decreasing addiction severity and gaming cravings compared with PMR. These findings indicate that MM may be an effective treatment for IGD and may exert its effects by altering frontopallidal pathways. Trial Registration: Chinese Clinical Trial Registry Identifier: ChiCTR2300075869.

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.

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.

Age-atypical brain functional networks in autism spectrum disorder: a normative modeling approach.

BACKGROUND: Despite extensive research into the neural basis of autism spectrum disorder (ASD), the presence of substantial biological and clinical heterogeneity among diagnosed individuals remains a major barrier. Commonly used case‒control designs assume homogeneity among subjects, which limits their ability to identify biological heterogeneity, while normative modeling pinpoints deviations from typical functional network development at individual level. METHODS: Using a world-wide multi-site database known as Autism Brain Imaging Data Exchange, we analyzed individuals with ASD and typically developed (TD) controls (total n = 1218) aged 5-40 years, generating individualized whole-brain network functional connectivity (FC) maps of age-related atypicality in ASD. We then used local polynomial regression to estimate a networkwise normative model of development and explored correlations between ASD symptoms and brain networks. RESULTS: We identified a subset exhibiting highly atypical individual-level FC, exceeding 2 standard deviation from the normative value. We also identified clinically relevant networks (mainly default mode network) at cohort level, since the outlier rates decreased with age in TD participants, but increased in those with autism. Moreover, deviations were linked to severity of repetitive behaviors and social communication symptoms. CONCLUSIONS: Individuals with ASD exhibit distinct, highly individualized trajectories of brain functional network development. In addition, distinct developmental trajectories were observed among ASD and TD individuals, suggesting that it may be challenging to identify true differences in network characteristics by comparing young children with ASD to their TD peers. This study enhances understanding of the biological heterogeneity of the disorder and can inform precision medicine.

The resting-state brain activity signatures for addictive disorders.

BACKGROUND: Addiction is a chronic and relapsing brain disorder. Despite numerous neuroimaging and neurophysiological studies on individuals with substance use disorder (SUD) or behavioral addiction (BEA), currently a clear neural activity signature for the addicted brain is lacking. METHODS: We first performed systemic coordinate-based meta-analysis and partial least-squares regression to identify shared or distinct brain regions across multiple addictive disorders, with abnormal resting-state activity in SUD and BEA based on 46 studies (55 contrasts), including regional homogeneity (ReHo) and low-frequency fluctuation amplitude (ALFF) or fractional ALFF. We then combined Neurosynth, postmortem gene expression, and receptor/transporter distribution data to uncover the potential molecular mechanisms underlying these neural activity signatures. FINDINGS: The overall comparison between addiction cohorts and healthy subjects indicated significantly increased ReHo and ALFF in the right striatum (putamen) and bilateral supplementary motor area, as well as decreased ReHo and ALFF in the bilateral anterior cingulate cortex and ventral medial prefrontal cortex, in the addiction group. On the other hand, neural activity in cingulate cortex, ventral medial prefrontal cortex, and orbitofrontal cortex differed between SUD and BEA subjects. Using molecular analyses, the altered resting activity recapitulated the spatial distribution of dopaminergic, GABAergic, and acetylcholine system in SUD, while this also includes the serotonergic system in BEA. CONCLUSIONS: These results indicate both common and distinctive neural substrates underlying SUD and BEA, which validates and supports targeted neuromodulation against addiction. FUNDING: This work was supported by the National Natural Science Foundation of China and Intramural Research Program of the National Institute on Drug Abuse, National Institutes of Health.

Ten years of research on the treatments of internet gaming disorder: A scoping review and directions for future research.

Background: Although internet gaming disorder (IGD) has been listed in section III of the DSM-5 for approximately 10 years, the study of treatments for IGD remains in early stages. Nonetheless, a summary of findings to date and discussion of future research needs are warranted. Methods: The current study reviewed scientific treatment studies with control groups and randomized controlled trials. We summarized the strengths and weaknesses of different treatment strategies and identified gaps in the research literature that may inform the direction of future research efforts. Results: Sixteen studies were reviewed. Existing treatment studies may be categorized into cognitive behavioural therapy (CBT), pharmacotherapies, non-invasive brain stimulation (NIBS), and others. Conclusions: CBT is the most widely studied treatment strategy for IGD thus far. Future studies should consider IGD-specific CBT treatment strategies. Medication-based treatment should be implemented with caution. NIBS is promising, and future studies should explore the most efficacious parameters and targets. In addition, studies should consider sex differences in the treatment of IGD.

rTMS effects on urges and severity of tobacco use disorder operate independently of a retrieval-extinction component and involve frontal-striatal pathways.

BACKGROUND: Although smoking remains a leading cause of preventable disease, the treatment options for smoking are limited. The present study evaluated the neural features underlying effects of repetitive transcranial magnetic stimulation (rTMS) for reducing smoking cravings. In addition, the efficacy of a simulated retrieval-extinction procedure to augment rTMS efficacy was examined. METHODS: Sixty-one individuals with tobacco use disorder (TUD) were randomized into three groups: classic rTMS, retrieval rTMS (viewed smoking videos before rTMS), and sham rTMS. rTMS was performed on the left dorsolateral prefrontal cortex (DLPFC) over 5 days using a standard figure-8 coil. Smoking cravings and brain responses to smoking cues were measured before and after rTMS treatment. Changes in functional connectivity (FC) among different brain regions were calculated. RESULTS: rTMS reduced smoking urges in TUD. Both active-rTMS groups demonstrated greater activations of the DLPFC, caudate, and bilateral insula relative to the sham group. Increased FC was observed between executive and reward network brain regions, and decreased FC was observed within reward network regions. Compared with standard rTMS, retrieval-extinction rTMS demonstrated similar outcomes and was associated with less activation of the medial frontal gyrus. CONCLUSIONS: rTMS increased activations in brain regions implicated in executive control and reward processing. Strengthened prefrontal-striatal pathway suggests that rTMS enhanced top-down control over smoking cravings. The retrieval-extinction process, although associated with some different and multiple similar neural correlates as the standard rTMS, did not enhance cessation outcomes.

Adverse childhood experiences predict internet gaming disorder in university students: the mediating role of resilience.

BACKGROUND: To investigate the relationship between adverse childhood experiences and internet gaming disorder (IGD) and the mediating role of resilience in the relationship between these two factors. METHODS: The adverse childhood experience scale, resilience scale and IGD Scale were administered to 9349 university students. Correlations and mediating effects were calculated among these scores. RESULTS: After controlling for sex and age, significant correlations among adverse childhood experiences, resilience and IGD were observed; resilience was a partial mediator variable in the relationship between adverse childhood experiences and IGD. CONCLUSIONS: The more adverse childhood experiences an individual has, the less their mental toughness and the greater their tendency to become addicted to internet games. Adverse childhood experiences can effectively predict IGD, and the risk of becoming addicted to the internet can be decreased by increasing one's mental toughness.

Resting state default mode network is associated with wise advising.

Default mode network (DMN) may be associated with wisdom (i.e., mature understanding of life featured by perspectival metacognition) when advising from a self-referential perspective due to the involvement of the DMN in reflecting on personal life experiences. After a resting-state functional MRI scan, 52 adults advised some youths going through life dilemmas, half from a second-person perspective and half from a third. After advising each youth, participants indicated the psychological distance they felt between themselves and the youth. The amplitude of low-frequency fluctuation (ALFF) was measured in the DMN during resting states. Moreover, trained raters rated the participants' advice on wisdom criteria (i.e., metacognitive humility (MH), meta-level flexibility, and perspective-taking). The results showed that participants felt a significantly smaller psychological distance from the youth when advising from the second- than the third-person perspective. Moreover, only when advising from the second-person perspective was MH associated with ALFF in regions within the DMN (i.e., right rostral anterior cingulate cortex (ACC) and left dorsomedial prefrontal cortex). The right rostral ACC showed a significantly greater association with MH from the second- than the third-person perspective. Therefore, resting-state DMN activities may be important for self-involved wisdom performance (e.g., giving advice directly to others).

Brain responses to positive and negative events in individuals with internet gaming disorder during real gaming.

Objective: This study sought to investigate brain responses to positive and negative events in individuals with internet gaming disorder (IGD) during real gaming as a direct assessment of the neural features of IGD. This investigation reflects the neural deficits in individuals with IGD while playing games, providing direct and effective targets for prevention and treatment of IGD. Methods: Thirty subjects with IGD and fifty-two matched recreational game use (RGU) subjects were scanned while playing an online game. Abnormal brain activities during positive and negative events were detected using a general linear model. Functional connectivity (FC) and correlation analyses between neural features and addiction severity were conducted to provide additional support for the underlying neural features. Results: Compared to the RGU subjects, the IGD subjects exhibited decreased activation in the dorsolateral prefrontal cortex (DLPFC) during positive events and decreased activation in the middle frontal gyrus (MFG), precentral gyrus and postcentral gyrus during negative events. Decreased FC between the DLPFC and putamen during positive events and between the MFG and amygdala during negative events were observed among the IGD subjects. Neural features and addiction severity were significantly correlated. Conclusions: Individuals with IGD exhibited deficits in regulating game craving, maladaptive habitual gaming behaviors and negative emotions when experiencing positive and negative events during real game-playing compared to RGU gamers. These abnormalities in neural substrates during real gaming provide direct evidence for explaining why individuals with IGD uncontrollably and continuously engage in game playing, despite negative consequences.

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.

Edge-centric functional network analyses reveal disrupted network configuration in autism spectrum disorder.

BACKGROUND: Neuroscientific evidence suggests that the pathological symptoms associated with autism spectrum disorders (ASD) are not confined to a single brain region but involve networks of the brain on a larger spatial scale. Analyzing diagrams of edge-edge interactions could provide important perspectives on the organization and function of complex systems. METHODS: Resting-state fMRI data from 238 ASD patients and 311 healthy controls (HCs) were included in the current study. We used the thalamus as the mediating node to calculate the edge functional connectivity (eFC) of the brain network and compared the ASD subjects and HCs. RESULTS: Compared with the HCs, the ASD subjects exhibited abnormalities in the central node thalamus and four brain regions (amygdala, nucleus accumbens, pallidum and hippocampus), as well as in the eFC formed by the inferior frontal gyrus (IFG) (or middle temporal gyrus (MTG)). In addition, ASD subjects showed variable characteristics of the eFC between nodes in different networks. CONCLUSIONS: The changes in these brain regions may be due to the disturbance in the reward system, which leads to coherence in the instantaneous comovement of the functional connections formed by these brain regions in ASD. This notion also reveals a functional network feature between the cortical and subcortical regions in ASD.

The involvement of spontaneous brain activity in natural recovery from internet gaming disorder: A resting-state fMRI study.

Objective: Internet gaming disorder (IGD) can seriously impair an individual's physical and mental health. However, unlike the majority of those suffering from substance addiction, individuals with IGD may recover without any professional intervention. Understanding the brain mechanisms of natural recovery from IGD may provide new insight into how to prevent addiction and implement more targeted interventions. Methods: Sixty individuals with IGD were scanned by using a resting-state fMRI to assess brain region changes associated with IGD. After 1 year, 19 individuals with IGD no longer met the IGD criteria and were considered recovered (RE-IGD), 23 individuals still met the IGD criteria (PER-IGD), and 18 individuals left the study. The brain activity in resting state between 19 RE-IGD individuals and 23 PER-IGD individuals was compared by using regional homogeneity (ReHo). Additionally, brain structure and cue-craving functional MRIs were collected to further support the results in the resting-state. Results: The resting-state fMRI results revealed that activity in brain regions responsible for reward and inhibitory control [including the orbitofrontal cortex (OFC), the precuneus and the dorsolateral prefrontal cortex (DLPFC)] was decreased in the PER-IGD individuals compared to RE-IGD individuals. In addition, significant positive correlations were found between mean ReHo values in the precuneus and self-reported craving scores for gaming, whether among the PER-IGD individuals or the RE-IGD individuals. Furthermore, we found similar results in that brain structure and cue-craving differences exist between the PER-IGD individuals and RE-IGD individuals, specifically in the brain regions associated with reward processing and inhibitory control (including the DLPFC, anterior cingulate gyrus, insula, OFC, precuneus, and superior frontal gyrus). Conclusion: These findings indicate that the brain regions responsible for reward processing and inhibitory control are different in PER-IGD individuals, which may have consequences on natural recovery. Our present study provides neuroimaging evidence that spontaneous brain activity may influence natural recovery from IGD.

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.

Disrupted network integration and segregation involving the default mode network in autism spectrum disorder.

Changes in the brain's default mode network (DMN) in the resting state are closely related to autism spectrum disorder (ASD). Module segmentation can effectively elucidate the neural mechanism of ASD and explore intra- and inter-network connections by means of the participation coefficient (PC). We used that resting-state fMRI data from 269 ASD patients and 340 healthy controls (HCs) in the current study. From the results, ASD subjects showed a significantly higher PC of the DMN than HC subjects. This difference was related to lower intra-module connections within the DMN and higher inter-network connections between the DMN and other networks. When the subjects were split into age groups, the results were verified in the 7-12- and 12-18-year-old age groups but not in the young adult group (18-25 years). When the subjects were divided according to different subtypes of ASD, the results were also observed in the classic autism and pervasive developmental disorder groups, but not in the Asperger disorder group. In conclusions, less developed network segregation in the DMN could be a valid biomarker for ASD. This provides network scientists with new insights into the intermodular connectivity configurations of complex networks from different dimensions in a systematic and comprehensive manner.

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.

Connectome-based prediction of the severity of autism spectrum disorder.

Background: Autism spectrum disorder (ASD) is characterized by social and behavioural deficits. Current diagnosis relies on behavioural criteria, but machine learning, particularly connectome-based predictive modelling (CPM), offers the potential to uncover neural biomarkers for ASD. Objective: This study aims to predict the severity of ASD traits using CPM and explores differences among ASD subtypes, seeking to enhance diagnosis and understanding of ASD. Methods: Resting-state functional magnetic resonance imaging data from 151 ASD patients were used in the model. CPM with leave-one-out cross-validation was conducted to identify intrinsic neural networks that predict Autism Diagnostic Observation Schedule (ADOS) scores. After the model was constructed, it was applied to independent samples to test its replicability (172 ASD patients) and specificity (36 healthy control participants). Furthermore, we examined the predictive model across different aspects of ASD and in subtypes of ASD to understand the potential mechanisms underlying the results. Results: The CPM successfully identified negative networks that significantly predicted ADOS total scores [r (df = 150) = 0.19, P = 0.008 in all patients; r (df = 104) = 0.20, P = 0.040 in classic autism] and communication scores [r (df = 150) = 0.22, P = 0.010 in all patients; r (df = 104) = 0.21, P = 0.020 in classic autism]. These results were reproducible across independent databases. The networks were characterized by enhanced inter- and intranetwork connectivity associated with the occipital network (OCC), and the sensorimotor network (SMN) also played important roles. Conclusions: A CPM based on whole-brain resting-state functional connectivity can predicted the severity of ASD. Large-scale networks, including the OCC and SMN, played important roles in the predictive model. These findings may provide new directions for the diagnosis and intervention of ASD, and maybe could be the targets in novel interventions.

Gender difference in network relationship between inter-temporal decisions and prefrontal activation levels in internet gaming disorder.

Background: Impulsivity and decision-making are key factors in addiction. However, little is known about how gender and time sensitivity affect impulsivity in internet gaming disorder (IGD). Objective: To investigate the gender difference of impulsive decision-making and relevant brain responses in IGD. Methods: We conducted a functional magnetic resonance imaging (fMRI) study with 123 participants, including 59 IGD individuals (26 females) and 64 matched recreational game users (RGUs, 23 females). Participants performed a delay-discounting task during fMRI scanning. We examined gender-by-group effects on behavioral and neural measures to explore the preference for immediate over delayed rewards and the associated brain activity. We also investigated the network correlations between addiction severity and behavioral and neural measures, and analyzed the mediating role of brain activity in the link between delay discounting parameters and IGD severity. Results: We found significant gender-by-group interactions. The imaging results revealed gender-by-group interactions in the dorsolateral prefrontal cortex, medial frontal gyrus, and inferior frontal gyrus (IFG). Post hoc analysis indicated that, for females, RGUs showed higher activity than IGD individuals in these brain regions, while for males IGD individuals exhibited higher activity than RGUs. The activation in the left IFG mediated the relation between Internet Addiction Test score and discount rate in females. In males, the activation in the right dlPFC mediated the relation between IAT score and time sensitivity. Discussion: Our findings imply that male IGD participants demonstrate impaired intertemporal decisions associated with neural dysfunction. Influencing factors for impulsive decision-making in IGD diverge between males (time sensitivity) and females (discount rate). These findings augment our comprehension of the neural underpinnings of gender differences in IGD and bear significant implications for devising effective intervention strategies for treating people with IGD.

Connectome-based predictive modelling of smoking severity in smokers.

The functional connectivity within and between networks could provide a framework to characterize the neurobiological mechanism of nicotine addiction. This study examined the brain regions that were functionally connected in response to smoking cues and established the brain-behaviour relationships in smokers. Sixty-seven male smokers were enrolled and scanned while performing the cue-reactivity and Stroop task. A whole-brain analysis approach, connectome-based predictive modelling (CPM), was conducted on the data from the cue-reactivity task to identify the networks that could predict the smoking severity with the Shen atlas as templates. Then, the brain-behaviour relationships were verified in a different brain state (Stroop task). CPM identified the smoking severity-related network, as indicated by a significant correlation between predicted and actual smoking severity scores (r = 0.31, p = 0.02). Identified networks mainly involved the canonical networks implicated in the reward process (motor/sensory network and salience network) and executive control (frontoparietal network). Network strength in the Stroop task marginally significantly predicted smoking severity scores (r = 0.23, p = 0.06), partially replicating the brain-behaviour relationship. The CPM results identified the whole-brain neural network related to smoking severity, which was cross-validated by the AAL and Shen atlas. These findings contribute to more profound insights into neural substrates underlying the smoking severity.