Hostname: page-component-5d59c44645-7l5rh Total loading time: 0 Render date: 2024-02-22T15:28:45.766Z Has data issue: false hasContentIssue false

Altered coupling of default-mode, executive-control and salience networks in Internet gaming disorder

Published online by Cambridge University Press:  23 March 2020

J.T. Zhang
State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, 100875Beijing, China
S.-S. Ma
State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, 100875Beijing, China
C.-G. Yan
Key Laboratory of Behavioral Science and Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, 100101Beijing, China
S. Zhang
Department of Psychiatry, Yale University School of MedicineNew Haven, CT06519, USA
L. Liu
Institute of Developmental Psychology, Beijing Normal University, Beijing100875, China
L.-J. Wang
State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, 100875Beijing, China
B. Liu
State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, 100875Beijing, China
Y.-W. Yao
State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, 100875Beijing, China
Y.-H. Yang
Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of HealthBaltimore, MD21224, USA
X.-Y. Fang*
Institute of Developmental Psychology, Beijing Normal University, Beijing100875, China
*Corresponding author. E-mail (X.-Y. Fang).
Get access



Recently, a triple-network model suggested the abnormal interactions between the executive-control network (ECN), default-mode network (DMN) and salience network (SN) are important characteristics of addiction, in which the SN plays a critical role in allocating attentional resources toward the ECN and DMN. Although increasing studies have reported dysfunctions in these brain networks in Internet gaming disorder (IGD), interactions between these networks, particularly in the context of the triple-network model, have not been investigated in IGD. Thus, we aimed to assess alterations in the inter-network interactions of these large-scale networks in IGD, and to associate the alterations with IGD-related behaviors.


DMN, ECN and SN were identified using group-level independent component analysis (gICA) in 39 individuals with IGD and 34 age and gender matched healthy controls (HCs). Then alterations in the SN-ECN and SN-DMN connectivity, as well as in the modulation of ECN versus DMN by SN, using a resource allocation index (RAI) developed and validated previously in nicotine addiction, were assessed. Further, associations between these altered network coupling and clinical assessments were also examined.


Compared with HCs, IGD had significantly increased SN-DMN connectivity and decreased RAI in right hemisphere (rRAI), and the rRAI in IGD was negatively associated with their scores of craving.


These findings suggest that the deficient modulation of ECN versus DMN by SN might provide a mechanistic framework to better understand the neural basis of IGD and might provide novel evidence for the triple-network model in IGD.

Original article
Copyright © European Psychiatric Association 2017

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)


Ha, JHYoo, HJCho, IHChin, BShin, DKim, JHPsychiatric comorbidity assessed in Korean children and adolescents who screen positive for Internet addiction. J Clin Psychiatry 2006;67:478826.CrossRefGoogle ScholarPubMed
Ko, C.-H.Liu, G.-C.Hsiao, SYen, J.-Y.Yang, M.-J.Lin, W.-C., et al.Brain activities associated with gaming urge of online gaming addiction. J Psychiatr Res 2009;43:739747.CrossRefGoogle ScholarPubMed
Ko, CHLiu, GCYen, JYChen, CYYen, CFChen, CSBrain correlates of craving for online gaming under cue exposure in subjects with Internet gaming addiction and in remitted subjects. Addict Biol 2013;18:559569.CrossRefGoogle ScholarPubMed
Grant, JEPotenza, MNWeinstein, AGorelick, DAIntroduction to behavioral addictions. Am J Drug Alcohol Abuse 2010;36:233241.CrossRefGoogle ScholarPubMed
Association, APDiagnostic and statistical manual of mental disorders, 5th ed, Washington, DC: American Psychiatric Association; 2013.CrossRefGoogle Scholar
Ding W-n, Sun J-h, Sun Y-w, Zhou, YLi, LXu J-r, , et al.Altered default network resting-state functional connectivity in adolescents with internet gaming addiction. PLoS One 2013;8.CrossRefGoogle Scholar
Du, XQi, XYang, YXDu, GJGao, PHZhang, Y, et al.Altered structural correlates of impulsivity in adolescents with internet gaming disorder. Front Hum Neurosci 2016;10.CrossRefGoogle Scholar
Wang, YYin, YSun, YWZhou, YChen, XDing, WN, et al.Decreased prefrontal lobe interhemispheric functional connectivity in adolescents with internet gaming disorder: a primary study using resting-state fMRI. PLoS One 2015;10.CrossRefGoogle Scholar
Zhang, JTYao, YWLi, CSRZang, YFShen, ZJLiu, L, et al.Altered resting-state functional connectivity of the insula in young adults with Internet gaming disorder. Addict Biol 2015CrossRefGoogle Scholar
Jin, CWZhang, TCai, CXBi, YZLi, YDYu, DH, et al.Abnormal prefrontal cortex resting state functional connectivity and severity of internet gaming disorder. Brain Imaging Behav 2016;10:719729.CrossRefGoogle ScholarPubMed
Wang, LXWu, LDLin, XZhang, YFZhou, HLDu, XX, et al.Altered brain functional networks in people with Internet gaming disorder: Evidence from resting-state fMRI. Psychiatry Res-Neuroimaging 2016;254:156163.CrossRefGoogle ScholarPubMed
Zhang, YZMei, WZhang, JXWu, QLZhang, WDecreased functional connectivity of insula-based network in young adults with internet gaming disorder. Exp Brain Res 2016;234:25532560.CrossRefGoogle ScholarPubMed
Park, HJFriston, KJStructural and functional brain networks: from connections to cognition. Science 2013;342:579.CrossRefGoogle Scholar
Damoiseaux, JSRombouts, S.A.R.B.Barkhof, FScheltens, PStam, CJSmith, SM, et al.Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci U S A 2006;103:1384813853.CrossRefGoogle ScholarPubMed
Power, JDCohen, ALNelson, SMWig, GSBarnes, KAChurch, JA, et al.Functional network organization of the human brain. Neuron 2011;72:665678.CrossRefGoogle ScholarPubMed
Smith, SMFox, PTMiller, KLGlahn, DCFox, PMMackay, CE, et al.Correspondence of the brain's functional architecture during activation and rest. Proc Natl Acad Sci U S A 2009;106:1304013045.CrossRefGoogle Scholar
Fox, MDSnyder, AZVincent, JLCorbetta, MVan Essen, DCRaichle, METhe human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A 2005;102:96739678.CrossRefGoogle ScholarPubMed
Xing, LHYuan, KBi, YZYin, JSCai, CXFeng, D, et al.Reduced fiber integrity and cognitive control in adolescents with internet gaming disorder. Brain Res 2014;1586:109117.CrossRefGoogle ScholarPubMed
Yuan, KQin, WYu, DHBi, YZXing, LHJin, CW, et al.Core brain networks interactions and cognitive control in internet gaming disorder individuals in late adolescence/early adulthood. Brain Struct Funct 2016;221:14271442.CrossRefGoogle ScholarPubMed
Dong, GLin, XHu, YXie, CDu, XImbalanced functional link between executive control network and reward network explain the online-game seeking behaviors in Internet gaming disorder. Sci Rep 2015;5.CrossRefGoogle Scholar
Chu-Shore, CJKramer, MABianchi, MTCaviness, VSCash, SSNetwork Analysis:, Applications for the developing brain. J Child Neurol 2011;26:488500.CrossRefGoogle ScholarPubMed
Sridharan, DLevitin, DJMenon, VA critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proc Natl Acad Sci 2008;105:1256912574.CrossRefGoogle ScholarPubMed
Menon, VLarge-scale brain networks and psychopathology: a unifying triple network model. Trends Cogn Sci 2011;15:483506.CrossRefGoogle ScholarPubMed
Sutherland, MTMcHugh, MJPariyadath, VStein, EAResting state functional connectivity in addiction: Lessons learned and a road ahead. Neuroimage 2012;62:22812295.CrossRefGoogle Scholar
Menon, VUddin, LQSaliency, switching, attention and control: a network model of insula function. Brain Struct Funct 2010;214:655667.CrossRefGoogle ScholarPubMed
Fox, MDGreicius, MClinical applications of resting state functional connectivity. Front Syst Neurosci 2010;4:19.Google ScholarPubMed
Raichle, MEMacLeod, AMSnyder, AZPowers, WJGusnard, DAShulman, GLA default mode of brain function. Proc Natl Acad Sci U S A 2001;98:676682.CrossRefGoogle ScholarPubMed
Seeley, WWMenon, VSchatzberg, AFKeller, JGlover, GHKenna, H, et al.Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci 2007;27:23492356.CrossRefGoogle ScholarPubMed
Arcurio, LRFinn, PRJames, TWNeural mechanisms of high-risk decisions to drink in alcohol-dependent women. Addict Biol 2015;20:390406.CrossRefGoogle ScholarPubMed
Lerman, CGu, HLoughead, JRuparel, KYang, YStein, EALarge-scale brain network coupling predicts acute nicotine abstinence effects on craving and cognitive function. JAMA psychiatry 2014;71:523530.CrossRefGoogle ScholarPubMed
Cho, HKwon, MChoi, J.-H.Lee, S.-K.Choi, JSChoi, S.-W., et al.Development of the Internet addiction scale based on the Internet Gaming Disorder criteria suggested in DSM-5. Addict Behav 2014;39:13611366.CrossRefGoogle ScholarPubMed
Ko, C.-H.Yen, J.-Y.Chen, S.-H.Yang, M.-J.Lin, H.-C.Yen, C.-F.Proposed diagnostic criteria and the screening and diagnosing tool of Internet addiction in college students. Compr psychiatry 2009;50:378384.CrossRefGoogle ScholarPubMed
Chen, SWeng, LSu, YWu, HYang, PDevelopment of a Chinese Internet addiction scale and its psychometric study. Chinese J Psychol 2003;45:279.Google Scholar
Lin, XDong, GWang, QDu, XAbnormal gray matter and white matter volume in ‘Internet gaming addicts’. Addict Behav 2015;40:137143.CrossRefGoogle ScholarPubMed
Fagerstrom, KOMeasuring degree of physical-dependence to tobacco smoking with reference to individualization of treatment. Addict Behav 1978;3:235241.CrossRefGoogle ScholarPubMed
Bush, KKivlahan, DRMcDonell, MBFihn, SDBradley, KAThe, AUDIT.alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Arch Intern Med 1998;158:17891795.CrossRefGoogle ScholarPubMed
Beck, ATBrown, GEpstein, NSteer, RAAn inventory for measuring clinical anxiety –psychometric properties. J Consult Clin Psych 1988;56:893897.CrossRefGoogle ScholarPubMed
Beck, ATErbaugh, JWard, CHMock, JMendelsohn, MAn inventory for measuring depression. Arch Gen Psychiat 1961;4 [561–&].CrossRefGoogle ScholarPubMed
Cox, LSTiffany, STChristen, AGEvaluation of the brief questionnaire of smoking urges (QSU-brief) in laboratory and clinical settings. Nicotine Tob Res 2001;3:716.CrossRefGoogle ScholarPubMed
Yan, CZang, YDPARSF: a MATLAB toolbox for“pipeline” data analysis of resting-state fMRI. Frontiers in systems neuroscience 2010;4:13.Google Scholar
Yan, CGCheung, BKelly, CColcombe, SCraddock, RCDi Martino, A, et al.A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics. Neuroimage 2013;76:183201.CrossRefGoogle ScholarPubMed
Murphy, KBirn, RMHandwerker, DAJones, TBBandettini, PAThe impact of global signal regression on resting state correlations: are anti-correlated networks introduced?. Neuroimage 2009;44:893905.CrossRefGoogle ScholarPubMed
Tahmasebi, AMAbolmaesumi, PZheng, ZZMunhall, KGJohnsrude, ISReducing inter-subject anatomical variation: effect of normalization method on sensitivity of functional magnetic resonance imaging data analysis in auditory cortex and the superior temporal region. NeuroImage 2009;47:15221531.CrossRefGoogle ScholarPubMed
Ding, XLee, SWChanges of functional and effective connectivity in smoking replenishment on deprived heavy smokers: a resting-state fMRI study. PLoS One 2013;8..CrossRefGoogle Scholar
Metin, BKrebs, RMWiersema, JRVerguts, TGasthuys, Rvan der Meere, JJ, et al.Dysfunctional modulation of default mode network activity in attention-deficit/hyperactivity disorder. J Abnormal Psychol 2015;124:208214.CrossRefGoogle ScholarPubMed
Zheng, HNXu, LLXie, FFGuo, XJZhang, JCYao, L, et al.The altered triple networks interaction in depression under resting state based on graph theory. Biomed Res Int 2015CrossRefGoogle Scholar
Wang, LWu, LLin, XZhang, YZhou, HDu, X, et al.Dysfunctional default mode network and executive control network in people with Internet gaming disorder: independent component analysis under a probability discounting task. European Psychiatr 2016;34:3642.CrossRefGoogle Scholar
Calhoun, VDLiu, JAdalı, TA review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data. Neuroimage 2009;45:S163S172.CrossRefGoogle ScholarPubMed
Calhoun, VAdali, TPearlson, GPekar, JA method for making group inferences from functional MRI data using independent component analysis. Human brain mapping 2001;14:140151.CrossRefGoogle ScholarPubMed
Bell, AJSejnowski, TJAn information-maximization approach to blind separation and blind deconvolution. Neural computation 1995;7(6):11291159.CrossRefGoogle ScholarPubMed
Himberg, JHyvärinen, AEsposito, FValidating the independent components of neuroimaging time series via clustering and visualization. Neuroimage 2004;22:12141222.CrossRefGoogle ScholarPubMed
Meda, SAStevens, MCFolley, BSCalhoun, VDPearlson, GDEvidence for anomalous network connectivity during working memory encoding in schizophrenia: an ICA based analysis. PLoS One 2009;4.CrossRefGoogle Scholar
Beckmann, CFDeLuca, MDevlin, JTSmith, SMInvestigations into resting-state connectivity using independent component analysis. Philos T Roy Soc B 2005;360:10011013.CrossRefGoogle ScholarPubMed
Cai, WChen, TSzegletes, LSupekar, KMenon, VAberrant cross-brain network interaction in children with attention-deficit/hyperactivity disorder and its relation to attention deficits: a multisite and cross-site replication study. Biological psychiatry 2015CrossRefGoogle Scholar
Liang, XHe, YSalmeron, BJGu, HStein, EAYang, YHInteractions between the Salience and Default-Mode Networks Are Disrupted in Cocaine Addiction. J Neurosci 2015;35:80818090.CrossRefGoogle ScholarPubMed
Laird, ARFox, PMEickhoff, SBTurner, JARay, KLMcKay, DR, et al.Behavioral interpretations of intrinsic connectivity networks. J Cogn Neurosci 2011;23:40224037.CrossRefGoogle ScholarPubMed
Kraemer, HCSource of false findings in published research studies: adjusting for covariates. JAMA psychiatry 2015CrossRefGoogle Scholar
Power, JDBarnes, KASnyder, AZSchlaggar, BLPetersen, SESpurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 2012;59:21422154.CrossRefGoogle ScholarPubMed
Power, JDMitra, ALaumann, TOSnyder, AZSchlaggar, BLPetersen, SEMethods to detect, characterize, and remove motion artifact in resting state fMRI. Neuroimage 2014;84:320341.CrossRefGoogle ScholarPubMed
Dosenbach, NUFair, DAMiezin, FMCohen, ALWenger, KKDosenbach, RA, et al.Distinct brain networks for adaptive and stable task control in humans. Proc Natl Acad Sci 2007;104(26):1107311078.CrossRefGoogle ScholarPubMed
He, XXQin, WLiu, YZhang, XQDuan, YYSong, JY, et al.Age-related decrease in functional connectivity of the right fronto-insular cortex with the central executive and default-mode networks in adults from young to middle age. Neurosci Lett 2013;544:7479.CrossRefGoogle ScholarPubMed
Greicius, MDKrasnow, BReiss, ALMenon, VFunctional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci U S A 2003;100:253258.CrossRefGoogle ScholarPubMed
Critchley, HDElliott, RMathias, CJDolan, RJNeural activity relating to generation and representation of galvanic skin conductance responses: a functional magnetic resonance imaging study. J Neurosci 2000;20:30333040.CrossRefGoogle ScholarPubMed
Camprodon, JAMartínez-Raga, JAlonso-Alonso, MShih, M.-C.Pascual-Leone, AOne session of high frequency repetitive transcranial magnetic stimulation (rTMS) to the right prefrontal cortex transiently reduces cocaine craving. Drug and alcohol dependence; 2007;86:9194.CrossRefGoogle Scholar
Knoch, DGianotti, LRPascual-Leone, ATreyer, VRegard, MHohmann, M, et al.Disruption of right prefrontal cortex by low-frequency repetitive transcranial magnetic stimulation induces risk-taking behavior. J Neurosci 2006;26:64696472.CrossRefGoogle ScholarPubMed
Pujol, JBlanco-Hinojo, LBatalla, ALopez-Sola, MHarrison, BJSoriano-Mas, C, et al.Functional connectivity alterations in brain networks relevant to self-awareness in chronic cannabis users. J Psychiatr Res 2014;51:6878.CrossRefGoogle ScholarPubMed
Maria, M.M.M.S.Hartwell, KJHanlon, CACanterberry, MLematty, TOwens, M, et al.Right anterior insula connectivity is important for cue-induced craving in nicotine-dependent smokers. Addict Biol 2015;20:407414.CrossRefGoogle Scholar
Fransson, PMarrelec, GThe precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: evidence from a partial correlation network analysis. Neuroimage 2008;42:11781184.CrossRefGoogle Scholar
Zhang, SLi, CSRTask-related, low-frequency task-residual, and resting state activity in the default mode network brain regions. Front Psychol 2012;3.CrossRefGoogle Scholar
Dalbudak, EEvren, CAldemir, STaymur, IEvren, BTopcu, MThe impact of sensation seeking on the relationship between attention deficit/hyperactivity symptoms and severity of Internet addiction risk. Psychiatry Res 2015CrossRefGoogle Scholar
Demirci, KAkgönül, MAkpinar, ARelationship of smartphone use severity with sleep quality, depression, and anxiety in university students. J Behav Addict 2015;4:8592.CrossRefGoogle ScholarPubMed
Reed, PVile, ROsborne, LARomano, MTruzoli, RProblematic internet usage and immune function. PLoS One 2015;10:e0134538.CrossRefGoogle ScholarPubMed
Moreno, MAJelenchick, LABreland, DJExploring depression and problematic internet use among college females: a multisite study. Comput Hum Behav 2015;49:601607.CrossRefGoogle Scholar
Błachnio, APrzepiórka, APantic, IInternet use. Facebook intrusion, and depression: results of a cross-sectional study. Eur Psychiatry 2015CrossRefGoogle Scholar
Hyun, GJHan, DHLee, YSKang, KDYoo, SKChung, U.-S., et al.Risk factors associated with online game addiction: a hierarchical model. Comput Hum Behav 2015;48:706713.CrossRefGoogle Scholar
Supplementary material: File

Zhang et al. supplementary material

Table S1-S3
Download Zhang et al. supplementary material(File)
File 20 KB
Submit a response


No Comments have been published for this article.