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Dysfunctional default mode network and executive control network in people with Internet gaming disorder: Independent component analysis under a probability discounting task

Published online by Cambridge University Press:  23 March 2020

L Wang
Affiliation:
Department of Psychology, Zhejiang Normal University, 688 Yingbin Road JinhuaZhejiang Province321004, PRChina
L Wu
Affiliation:
Department of Psychology, University of Konstanz, Konstanz, Germany
X Lin
Affiliation:
Department of Psychology, Zhejiang Normal University, 688 Yingbin Road JinhuaZhejiang Province321004, PRChina Center for Life Science, Peking University, Beijing, PRChina
Y Zhang
Affiliation:
Department of Psychology, Zhejiang Normal University, 688 Yingbin Road JinhuaZhejiang Province321004, PRChina
H Zhou
Affiliation:
Department of Psychology, Zhejiang Normal University, 688 Yingbin Road JinhuaZhejiang Province321004, PRChina
X Du
Affiliation:
Department of Physics, Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, PRChina
G Dong
Affiliation:
Department of Psychology, Zhejiang Normal University, 688 Yingbin Road JinhuaZhejiang Province321004, PRChina
Corresponding
E-mail address:
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Abstract

Background

The present study identified the neural mechanism of risky decision-making in Internet gaming disorder (IGD) under a probability discounting task.

Methods

Independent component analysis was used on the functional magnetic resonance imaging data from 19 IGD subjects (22.2 ± 3.08 years) and 21 healthy controls (HC, 22.8 ± 3.5 years).

Results

For the behavioral results, IGD subjects prefer the risky to the fixed options and showed shorter reaction time compared to HC. For the imaging results, the IGD subjects showed higher task-related activity in default mode network (DMN) and less engagement in the executive control network (ECN) than HC when making the risky decisions. Also, we found the activities of DMN correlate negatively with the reaction time and the ECN correlate positively with the probability discounting rates.

Conclusions

The results suggest that people with IGD show altered modulation in DMN and deficit in executive control function, which might be the reason for why the IGD subjects continue to play online games despite the potential negative consequences.

Type
Original article
Copyright
Copyright © European Psychiatry 2016

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References

Young, KSInternet addiction: the emergence of a new clinical disorder. CyberPsychol Behav 1998;1(3):237244.CrossRefGoogle Scholar
Niemz, KGriffiths, MBanyard, PPrevalence of pathological Internet use among university students and correlations with self-esteem, the General Health Questionnaire (GHQ), and disinhibition. CyberPsychol Behav 2005;8(6):562570.CrossRefGoogle Scholar
Dong, GLu, QZhou, HZhao, XPrecursor or sequela: pathological disorders in people with Internet addiction disorder 2011.Google ScholarPubMed
Association, D-A.P.Diagnostic and statistical manual of mental disorders Arlington: American Psychiatric Publishing; 2013.CrossRefGoogle Scholar
Petry, NMO’Brien, CPInternet gaming disorder and the DSM-5. Addiction 2013;108(7):11861187.CrossRefGoogle ScholarPubMed
Johansson, AGötestam, KGProblems with computer games without monetary reward: similarity to pathological gambling 1, 2. Psychol Rep 2004;95(2):641650.CrossRefGoogle Scholar
Griffiths, MRelationship between gambling and video-game playing: a response to johansson and gotestam 1. Psychol Rep 2005;96(3):644646.CrossRefGoogle Scholar
Achab, SNicolier, MMauny, FMonnin, JTrojak, BVandel, Pet al.Massively multiplayer online role-playing games: comparing characteristics of addict vs. non-addict online recruited gamers in a French adult population. BMC Psychiatry 2011;11(1):144CrossRefGoogle Scholar
Gentile, DAChoo, HLiau, ASim, TLi, DFung, Det al.Pathological video game use among youths: a two-year longitudinal study. Pediatrics 2011;127(2):e319e329.CrossRefGoogle ScholarPubMed
Ko, C.-H.Internet gaming disorder. Curr Addict Rep 2014;1(3):177185.CrossRefGoogle Scholar
Gilman, JMCalderon, VCurran, MTEvins, AEYoung adult cannabis users report greater propensity for risk-taking only in non-monetary domains. Drug Alcohol Depend 2015;147: 2631.CrossRefGoogle ScholarPubMed
Madden, GJPetry, NMJohnson, PSPathological gamblers discount probabilistic rewards less steeply than matched controls. Exp Clin Psychopharmacol 2009;17(5):283CrossRefGoogle ScholarPubMed
Schutter, DJVan Bokhoven, IVanderschuren, LJLochman, JEMatthys, WRisky decision making in substance dependent adolescents with a disruptive behavior disorder. J Abnorm Child Psychol 2011;39(3):333339.CrossRefGoogle ScholarPubMed
Bari, ARobbins, TWInhibition and impulsivity: behavioral and neural basis of response control. Prog Neurobiol 2013;108: 4479.CrossRefGoogle ScholarPubMed
Yi, RChase, WDBickel, WKProbability discounting among cigarette smokers and nonsmokers: molecular analysis discerns group differences. Behav Pharmacol 2007;18(7):633639.CrossRefGoogle ScholarPubMed
Lin, XZhou, HDong, GDu, XImpaired risk evaluation in people with Internet gaming disorder: fMRI evidence from a probability discounting task. Prog Neuropsychopharmacol Biol Psychiatry 2015;56: 142148.CrossRefGoogle ScholarPubMed
Young, KInternet addiction test (IAT). Center for internet addiction Uzyskane 2009. 25(07)Google Scholar
Petry, NMRehbein, FGentile, DALemmens, JSRumpf, HJMößle, Tet al.An international consensus for assessing internet gaming disorder using the new DSM-5 approach. Addiction 2014;109(9):13991406.CrossRefGoogle ScholarPubMed
Widyanto, LMcMurran, MThe psychometric properties of the internet addiction test. CyberPsychol Behav 2004;7(4):443450.CrossRefGoogle ScholarPubMed
Widyanto, LGriffiths, MDBrunsden, VA psychometric comparison of the Internet Addiction Test, the Internet-Related Problem Scale, and self-diagnosis. Cyberpsychol Behav Soc Netw 2011;14(3):141149.CrossRefGoogle ScholarPubMed
Rachlin, HRaineri, ACross, DSubjective probability and delay. J Exp Anal Behav 1991;55(2):233CrossRefGoogle Scholar
Mitchell, SHMeasures of impulsivity in cigarette smokers and non-smokers. Psychopharmacology 1999;146(4):455464.CrossRefGoogle ScholarPubMed
Reynolds, BRichards, JBHorn, KKarraker, KDelay discounting and probability discounting as related to cigarette smoking status in adults. Behav Proc 2004;65(1):3542.CrossRefGoogle ScholarPubMed
Calhoun, VAdali, TPearlson, GPekar, JA method for making group inferences from functional MRI data using independent component analysis. Human Brain Mapp 2001;14(3):140151.CrossRefGoogle ScholarPubMed
Bell, AJSejnowski, TJAn information-maximization approach to blind separation and blind deconvolution. Neural Comput 1995;7(6):11291159.CrossRefGoogle ScholarPubMed
Himberg, JHyvärinen, AEsposito, FValidating the independent components of neuroimaging time series via clustering and visualization. Neuroimage 2004;22(3):12141222.CrossRefGoogle ScholarPubMed
McKeown, MJHansen, LKSejnowsk, TJIndependent component analysis of functional MRI: what is signal and what is noise?. Curr Opin Neurobiol 2003;13(5):620629.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(11):e7911CrossRefGoogle ScholarPubMed
Myerson, JGreen, LDiscounting of delayed rewards: models of individual choice. J Exp Anal Behav 1995;64(3):263276.CrossRefGoogle ScholarPubMed
Shirer, WRyali, SRykhlevskaia, EMenon, VGreicius, MDecoding subject-driven cognitive states with whole-brain connectivity patterns. Cerebral Cortex 2012;22(1):158165.CrossRefGoogle ScholarPubMed
Buckner, RLAndrews-Hanna, JRSchacter, DLThe brain’s default network. Ann N Y Acad Sci 2008;1124(1):138.CrossRefGoogle ScholarPubMed
Fox, MDRaichle, MESpontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 2007;8(9):700711.CrossRefGoogle ScholarPubMed
Raichle, MEMacLeod, AMSnyder, AZPowers, WJGusnard, DAShulman, GLA default mode of brain function. Proc Natl Acad Sci U S A 2001;98(2):676682.CrossRefGoogle ScholarPubMed
Pomarol-Clotet, ESalvador, RSarro, SGomar, JVila, FMartinez, Aet al.Failure to deactivate in the prefrontal cortex in schizophrenia: dysfunction of the default mode network?. Psychol Med 2008;38(08):11851193.CrossRefGoogle ScholarPubMed
Tian, LJiang, TWang, YZang, YHe, YLiang, Met al.Altered resting-state functional connectivity patterns of anterior cingulate cortex in adolescents with attention deficit hyperactivity disorder. Neurosci Lett 2006;400(1):3943.CrossRefGoogle ScholarPubMed
Greicius, MDFlores, BHMenon, VGlover, GHSolvason, HBKenna, Het al.Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry 2007;62(5):429437.CrossRefGoogle ScholarPubMed
Greicius, MDSrivastava, GReiss, ALMenon, VDefault-mode network activity distinguishes Alzheimer’s disease from healthy aging: evidence from functional MRI. Proc Natl Acad Sci U S A 2004;101(13):46374642.CrossRefGoogle ScholarPubMed
Ma, NLiu, YFu, X.-M.Li, NWang, C.-X.Zhang, Het al.Abnormal brain default-mode network functional connectivity in drug addicts. PLoS One 2011;6(1):e16560CrossRefGoogle ScholarPubMed
Arcurio, LRFinn, PRJames, TWNeural mechanisms of high-risk decisions-to-drink in alcohol-dependent women. Addict Biol 2015;20(2):390406.CrossRefGoogle ScholarPubMed
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(27):96739678.CrossRefGoogle ScholarPubMed
Fransson, PHow default is the default mode of brain function?: Further evidence from intrinsic BOLD signal fluctuations. Neuropsychologia 2006;44(14):28362845.CrossRefGoogle ScholarPubMed
Polli, FEBarton, JJCain, MSThakkar, KNRauch, SLManoach, DSRostral and dorsal anterior cingulate cortex make dissociable contributions during antisaccade error commission. Proc Natl Acad Sci U S A 2005;102(43):1570015705.CrossRefGoogle ScholarPubMed
Weissman, DRoberts, KVisscher, KWoldorff, MThe neural bases of momentary lapses in attention. Nat Neurosci 2006;9(7):971978.CrossRefGoogle ScholarPubMed
Schiebener, JGarcía-Arias, MGarcía-Villamisar, DCabanyes-Truffino, JBrand, MDevelopmental changes in decision making under risk: the role of executive functions and reasoning abilities in 8- to 19-year-old decision makers. Child Neuropsychol 2014 120 [ahead-of-print]Google ScholarPubMed
Euteneuer, FSchaefer, FStuermer, RBoucsein, WTimmermann, LBarbe, MTet al.Dissociation of decision-making under ambiguity and decision-making under risk in patients with Parkinson’s disease: a neuropsychological and psychophysiological study. Neuropsychologia 2009;47(13):28822890.CrossRefGoogle ScholarPubMed
Brand, MLabudda, KMarkowitsch, HJNeuropsychological correlates of decision-making in ambiguous and risky situations. Neural Netw 2006;19(8):12661276.CrossRefGoogle ScholarPubMed
Brand, MFujiwara, EBorsutzky, SKalbe, EKessler, JMarkowitsch, HJDecision-making deficits of korsakoff patients in a new gambling task with explicit rules: associations with executive functions. Neuropsychology 2005;19(3):267CrossRefGoogle Scholar
Schiebener, JWegmann, EGathmann, BLaier, CPawlikowski, MBrand, MAmong three different executive functions, general executive control ability is a key predictor of decision making under objective risk. Front Psychol 2014 5Google ScholarPubMed
Dong, GHu, YLin, XLu, QWhat makes Internet addicts continue playing online even when faced by severe negative consequences? Possible explanations from an fMRI study. Biol Psychol 2013;94(2):282289.CrossRefGoogle ScholarPubMed
Dong, GDeVito, EEDu, XCui, ZImpaired inhibitory control in ‘internet addiction disorder’: a functional magnetic resonance imaging study. Psychiatry Res 2012;203(2):153158.CrossRefGoogle ScholarPubMed
Dong, GZhou, HZhao, XMale Internet addicts show impaired executive control ability: evidence from a color-word Stroop task. Neurosci Lett 2011;499(2):114118.CrossRefGoogle ScholarPubMed
Dong, GLin, XPotenza, MNDecreased functional connectivity in an executive control network is related to impaired executive function in Internet gaming disorder. Prog neuropsychopharmacol Biol Psychiatry 2015;57: 7685.CrossRefGoogle Scholar
Hester, RLubman, DIYücel, MThe role of executive control in human drug addiction. Behavioral Neuroscience of Drug Addiction Springer; 2010. 301318.CrossRefGoogle Scholar
Dong, GHu, YLin, XReward/punishment sensitivities among internet addicts: implications for their addictive behaviors. Prog neuropsychopharmacol Biol Psychiatry 2013;46: 139145.CrossRefGoogle ScholarPubMed
Everitt, BJHutcheson, DMErsche, KDPelloux, YDalley, JWRobbins, TWThe orbital prefrontal cortex and drug addiction in laboratory animals and humans. Ann N Y Acad Sci 2007;1121(1):576597.CrossRefGoogle ScholarPubMed
Goldstein, RZVolkow, NDDysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nat Rev Neurosci 2011;12(11):652669.CrossRefGoogle ScholarPubMed
Sofuoglu, MDeVito, EEWaters, AJCarroll, KMCognitive enhancement as a treatment for drug addictions. Neuropharmacology 2013;64: 452463.CrossRefGoogle ScholarPubMed
Dong, GLin, XZhou, HLu, QCognitive flexibility in Internet addicts: fMRI evidence from difficult-to-easy and easy-to-difficult switching situations. Addict Behav 2014;39(3):677683.CrossRefGoogle ScholarPubMed
Dong, GHuang, JDu, XEnhanced reward sensitivity and decreased loss sensitivity in Internet addicts: an fMRI study during a guessing task. J Psychiatric Res 2011;45(11):15251529.CrossRefGoogle ScholarPubMed
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