Background: Patients with Internet gaming disorder (IGD) and attention-deficit/hyperactivity disorder (ADHD) have high comorbidity but it is still unknown whether these disorders have shared and distinctive neuroimage alterations.Objective: The aim of this meta-analysis was to identify shared and disorder-specific structural, functional, and multimodal abnormalities between IGD and ADHD.Methods: A systematic literature search was conducted for whole-brain voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies comparing people with IGD or ADHD with healthy controls. Regional gray matter volume (GMV) and fMRI differences were compared over the patient groups and then a quantitative comparison was performed to find abnormalities (relative to controls) between IGD and ADHD using seed-based d mapping meta-analytic methods.Result: The meta-analysis contained 14 IGD VBM studies (contrasts covering 333 IGDs and 335 HCs), 26 ADHD VBM studies (1,051 patients with ADHD and 887 controls), 30 IGD fMRI studies (603 patients with IGD and 564 controls), and 29 ADHD fMRI studies (878 patients with ADHD and 803 controls). Structurally, VBM analysis showed disorder-specific GMV abnormality in the putamen among IGD subjects and orbitofrontal cortex in ADHD and shared GMV in the prefrontal cortex. Functionally, fMRI analysis discovered that IGD-differentiating increased activation in the precuneus and shared abnormal activation in anterior cingulate cortex, insular, and striatum.Conclusion: IGD and ADHD have shared and special structural and functional alterations. IGD has disorder-differentiating structural alterations in the putamen and ADHD has alterations in the orbitofrontal cortex. Disorder-differentiating fMRI activations were predominantly observed in the precuneus among IGD subjects and shared impairing function connection was in the rewards circuit (including ACC, OFC, and striatum).
Smoking is companied with altered intrinsic activity of the brain measured by amplitude of low‐frequency fluctuation. Evidence has revealed that human brain activity is a highly dynamic and rapidly changing system. How exactly cigarette smoking affect temporal dynamic intrinsic brain activity is not fully understood nor is it clear how smoking severity influences spontaneous brain activity. Dynamic amplitude of low‐frequency fluctuation (dALFF) was used to examine the dynamic temporal variability in 93 participants (63 smokers, 30 nonsmokers). We further divided smokers into light and heavy smokers. The temporal variability in intrinsic brain activity among these groups was compared. Correlation analyses were performed between dALFF in areas showing group differences and smoking behaviour (e.g., the Fagerström Test for Nicotine Dependence [FTND] scores and pack‐years). Smokers showed significantly increased dALFF in the left inferior/middle frontal gyrus, right orbitofrontal gyrus, right insula, left superior/medial frontal gyrus and right middle frontal gyrus than nonsmokers. Light smokers showed increased dALFF variability in the left prefrontal cortex. Heavy smokers showed increased dynamics in specific brain regions, including the right postcentral gyrus, right insula and left precentral gyrus. Furthermore, the temporal variability in dALFF in the left superior/medial frontal gyrus, left superior/middle frontal gyrus, right middle frontal gyrus and right insula was positively correlated with pack‐years or FTND. Combined, these results suggest that smokers increase stable and persistent spontaneous brain activity in prefrontal cortex, involved impaired gold‐directed action and value‐based decision‐making. In addition, individuals with heavier smoking severity show increased perturbance on spontaneous brain activity of perception and sensorimotor, related to increased reliance.
Previous studies have implicated abnormal functional coordination in brain regions of smokers. Neuroimaging studies demonstrated alternations in brain connectivity by using the resting-state functional connectivity (rsFC) method which arbitrarily chooses specific networks or seed regions as priori selections and cannot provide a full picture of the FC changes in chronic smokers. The aim of this study was to investigate the whole-brain functional coordination measured by functional connectivity density (FCD). As the variance of brain activity, dynamic FCD (dFCD) was performed to investigate dynamic changes of whole-brain integration in chronic smokers. In total, 120 chronic smokers and 56 nonsmokers were recruited, and static FCD and dFCD were performed to investigate aberrance of whole-brain functional coordination. Shared aberrance in visual areas has been found in both static and dFCD study in chronic smokers. Furthermore, the results exhibited that both heavy and light smokers demonstrated decreased dFCD in the visual cortex and left precuneus, and also increased dFCD in the right orbitofrontal cortex, left caudate, right putamen, and left thalamus compared with nonsmokers. In addition, alternations of dFCD have been found between heavy and light smokers. Furthermore, the dFCD variations showed significant positive correlation with smoking-related behaviors. The results demonstrated that chronic smokers not only have some initial areas, but also have some regions associated with severity of cigarette smoking. Lastly, dFCD could provide more subtle variations in chronic smokers, and the combination of static and dFCD may deepen our understanding of the brain alternations in chronic smokers.
Departmental sources Background: The tract-based spatial statistics (TBSS) method was used to investigate the changes of white matter microstructure in tobacco addicts, and to analyze its correlation with smoking index, smoking years, and daily smoking amount. Material/Methods: Routine magnetic resonance imaging (excluding intracranial lesions) and diffusion tensor imaging (DTI) sequence scanning were performed in 156 nicotine addicts (nicotine dependence group) and 81 non-nicotine addicts (control group) recruited from the study group. TBSS method was used to preprocess DTI data, and age and education level were taken as covariables to statistically analyze relevant parameters between nicotine dependence group and control group, such as fractional anisotropy (FA) value and smoking index. Spearman correlation analysis was performed on smoking status and FA values in brain regions with significant differences between nicotine dependent group and control group, and the test level a was 0.05. Results: Compared with control group, FA values of white matter in part of the posterior limb of the right inner capsule (r=-0.428, P=0.003), the right superior radiating crown (r=-0.136, P=0.004), the right posterior radiating crown (r=-0.229, P=0.003), the right superior longitudinal bundle (r=-0.474, P=0.002), the right inferior longitudinal bundle (r=-0.354, P=0.003) and the inferior frontal occipital bundle (r=-0.310, P=0.002) were decreased, which were negatively correlated with smoking index (P<0.05). Conclusions: Nicotine can damage the microstructure of white matter in specific brain regions and damage neurons, with cumulative effects.
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