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

European Psychiatry

Volumn 34, Issue , 2016, Pages 36-42

  Wang, L ^a   Wu, L ^c   Lin, X ^a,b   Zhang, Y ^a   Zhou, H ^a   Du, X ^d   Dong, G ^a  

^a ZHEJIANG NORMAL UNIVERSITY   (China)

^b PEKING UNIVERSITY   (China)

^c UNIVERSITY OF KONSTANZ   (Germany)

^d EAST CHINA NORMAL UNIVERSITY   (China)

Author keywords

Default mode network; Executive control network; Independent component analysis; Internet gaming disorder; Risky decision making

Indexed keywords

ADULT; ARTICLE; BEHAVIOR CHANGE; BRAIN DISEASE; CLINICAL ARTICLE; COGNITIVE FUNCTION TEST; CONTROLLED STUDY; CORRELATIONAL STUDY; DECISION MAKING; DEFAULT MODE NETWORK; DELAY DISCOUNTING; ELECTROENCEPHALOGRAM; EXECUTIVE FUNCTION; FUNCTIONAL MAGNETIC RESONANCE IMAGING; FUNCTIONAL NEUROIMAGING; HIGH RISK BEHAVIOR; HUMAN; INDEPENDENT COMPONENT ANALYSIS; INTERNET ADDICTION; MALE; NUCLEAR MAGNETIC RESONANCE SCANNER; PRIORITY JOURNAL; PROBABILITY DISCOUNTING TASK; RESPONSE TIME; YOUNG ADULT; ADDICTION; CASE CONTROL STUDY; FEMALE; INTERNET; PHYSIOLOGY; PROBABILITY; PSYCHOLOGY; REACTION TIME; VIDEO GAME;

ADULT; BEHAVIOR, ADDICTIVE; CASE-CONTROL STUDIES; DECISION MAKING; EXECUTIVE FUNCTION; FEMALE; HUMANS; INTERNET; MALE; PROBABILITY; REACTION TIME; VIDEO GAMES; YOUNG ADULT;

EID: 84959108527     PISSN: 09249338     EISSN: 17783585     Source Type: Journal    
DOI: 10.1016/j.eurpsy.2016.01.2424     Document Type: Article

References (59)

1. Young K.S. Internet addiction: the emergence of a new clinical disorder. CyberPsychol Behav 1998, 1(3):237-244.
2. Niemz K., Griffiths M., Banyard P. Prevalence of pathological Internet use among university students and correlations with self-esteem, the General Health Questionnaire (GHQ), and disinhibition. CyberPsychol Behav 2005, 8(6):562-570.
3. Dong G., Lu Q., Zhou H., Zhao X. Precursor or sequela: pathological disorders in people with Internet addiction disorder 2011.
4. Association D-A.P. Diagnostic and statistical manual of mental disorders 2013, American Psychiatric Publishing, Arlington.
5. Petry N.M., O'Brien C.P. Internet gaming disorder and the DSM-5. Addiction 2013, 108(7):1186-1187.
6. Johansson A., Götestam K.G. Problems with computer games without monetary reward: similarity to pathological gambling 1, 2. Psychol Rep 2004, 95(2):641-650.
7. Griffiths M. Relationship between gambling and video-game playing: a response to johansson and gotestam 1. Psychol Rep 2005, 96(3):644-646.
8. Achab S., Nicolier M., Mauny F., Monnin J., Trojak B., Vandel P., et 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):144.
9. Gentile D.A., Choo H., Liau A., Sim T., Li D., Fung D., et al. Pathological video game use among youths: a two-year longitudinal study. Pediatrics 2011, 127(2):e319-e329.
10. Ko C.-H. Internet gaming disorder. Curr Addict Rep 2014, 1(3):177-185.
11. Gilman J.M., Calderon V., Curran M.T., Evins A.E. Young adult cannabis users report greater propensity for risk-taking only in non-monetary domains. Drug Alcohol Depend 2015, 147:26-31.
12. Madden G.J., Petry N.M., Johnson P.S. Pathological gamblers discount probabilistic rewards less steeply than matched controls. Exp Clin Psychopharmacol 2009, 17(5):283.
13. Schutter D.J., Van Bokhoven I., Vanderschuren L.J., Lochman J.E., Matthys W. Risky decision making in substance dependent adolescents with a disruptive behavior disorder. J Abnorm Child Psychol 2011, 39(3):333-339.
14. Bari A., Robbins T.W. Inhibition and impulsivity: behavioral and neural basis of response control. Prog Neurobiol 2013, 108:44-79.
15. Yi R., Chase W.D., Bickel W.K. Probability discounting among cigarette smokers and nonsmokers: molecular analysis discerns group differences. Behav Pharmacol 2007, 18(7):633-639.
16. Lin X., Zhou H., Dong G., Du X. Impaired risk evaluation in people with Internet gaming disorder: fMRI evidence from a probability discounting task. Prog Neuropsychopharmacol Biol Psychiatry 2015, 56:142-148.
17. Young K. Internet addiction test (IAT). Center for internet addiction Uzyskane 2009, 25(07).
18. Petry N.M., Rehbein F., Gentile D.A., Lemmens J.S., Rumpf H.J., Mößle T., et al. An international consensus for assessing internet gaming disorder using the new DSM-5 approach. Addiction 2014, 109(9):1399-1406.
19. Widyanto L., McMurran M. The psychometric properties of the internet addiction test. CyberPsychol Behav 2004, 7(4):443-450.
20. Widyanto L., Griffiths M.D., Brunsden V. A psychometric comparison of the Internet Addiction Test, the Internet-Related Problem Scale, and self-diagnosis. Cyberpsychol Behav Soc Netw 2011, 14(3):141-149.
21. Rachlin H., Raineri A., Cross D. Subjective probability and delay. J Exp Anal Behav 1991, 55(2):233.
22. Mitchell S.H. Measures of impulsivity in cigarette smokers and non-smokers. Psychopharmacology 1999, 146(4):455-464.
23. Reynolds B., Richards J.B., Horn K., Karraker K. Delay discounting and probability discounting as related to cigarette smoking status in adults. Behav Proc 2004, 65(1):35-42.
24. Calhoun V., Adali T., Pearlson G., Pekar J. A method for making group inferences from functional MRI data using independent component analysis. Human Brain Mapp 2001, 14(3):140-151.
25. Bell A.J., Sejnowski T.J. An information-maximization approach to blind separation and blind deconvolution. Neural Comput 1995, 7(6):1129-1159.
26. Himberg J., Hyvärinen A., Esposito F. Validating the independent components of neuroimaging time series via clustering and visualization. Neuroimage 2004, 22(3):1214-1222.
27. McKeown M.J., Hansen L.K., Sejnowsk T.J. Independent component analysis of functional MRI: what is signal and what is noise?. Curr Opin Neurobiol 2003, 13(5):620-629.
28. Meda S.A., Stevens M.C., Folley B.S., Calhoun V.D., Pearlson G.D. Evidence for anomalous network connectivity during working memory encoding in schizophrenia: an ICA based analysis. PLoS One 2009, 4(11):e7911.
29. Myerson J., Green L. Discounting of delayed rewards: models of individual choice. J Exp Anal Behav 1995, 64(3):263-276.
30. Shirer W., Ryali S., Rykhlevskaia E., Menon V., Greicius M. Decoding subject-driven cognitive states with whole-brain connectivity patterns. Cerebral Cortex 2012, 22(1):158-165.
31. Buckner R.L., Andrews-Hanna J.R., Schacter D.L. The brain's default network. Ann N Y Acad Sci 2008, 1124(1):1-38.
32. Fox M.D., Raichle M.E. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 2007, 8(9):700-711.
33. Raichle M.E., MacLeod A.M., Snyder A.Z., Powers W.J., Gusnard D.A., Shulman G.L. A default mode of brain function. Proc Natl Acad Sci U S A 2001, 98(2):676-682.
34. Pomarol-Clotet E., Salvador R., Sarro S., Gomar J., Vila F., Martinez A., et al. Failure to deactivate in the prefrontal cortex in schizophrenia: dysfunction of the default mode network?. Psychol Med 2008, 38(08):1185-1193.
35. Tian L., Jiang T., Wang Y., Zang Y., He Y., Liang M., et al. Altered resting-state functional connectivity patterns of anterior cingulate cortex in adolescents with attention deficit hyperactivity disorder. Neurosci Lett 2006, 400(1):39-43.
36. Greicius M.D., Flores B.H., Menon V., Glover G.H., Solvason H.B., Kenna H., et al. Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry 2007, 62(5):429-437.
37. Greicius M.D., Srivastava G., Reiss A.L., Menon V. Default-mode network activity distinguishes Alzheimer's disease from healthy aging: evidence from functional MRI. Proc Natl Acad Sci U S A 2004, 101(13):4637-4642.
38. Ma N., Liu Y., Fu X.-M., Li N., Wang C.-X., Zhang H., et al. Abnormal brain default-mode network functional connectivity in drug addicts. PLoS One 2011, 6(1):e16560.
39. Arcurio L.R., Finn P.R., James T.W. Neural mechanisms of high-risk decisions-to-drink in alcohol-dependent women. Addict Biol 2015, 20(2):390-406.
40. Fox M.D., Snyder A.Z., Vincent J.L., Corbetta M., Van Essen D.C., Raichle M.E. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A 2005, 102(27):9673-9678.
41. Fransson P. How default is the default mode of brain function?: Further evidence from intrinsic BOLD signal fluctuations. Neuropsychologia 2006, 44(14):2836-2845.
42. Polli F.E., Barton J.J., Cain M.S., Thakkar K.N., Rauch S.L., Manoach D.S. Rostral and dorsal anterior cingulate cortex make dissociable contributions during antisaccade error commission. Proc Natl Acad Sci U S A 2005, 102(43):15700-15705.
43. Weissman D., Roberts K., Visscher K., Woldorff M. The neural bases of momentary lapses in attention. Nat Neurosci 2006, 9(7):971-978.
44. Schiebener J., García-Arias M., García-Villamisar D., Cabanyes-Truffino J., Brand M. Developmental 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, 1-20. [ahead-of-print].
45. Euteneuer F., Schaefer F., Stuermer R., Boucsein W., Timmermann L., Barbe M.T., et 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):2882-2890.
46. Brand M., Labudda K., Markowitsch H.J. Neuropsychological correlates of decision-making in ambiguous and risky situations. Neural Netw 2006, 19(8):1266-1276.
47. Brand M., Fujiwara E., Borsutzky S., Kalbe E., Kessler J., Markowitsch H.J. Decision-making deficits of korsakoff patients in a new gambling task with explicit rules: associations with executive functions. Neuropsychology 2005, 19(3):267.
48. Schiebener J., Wegmann E., Gathmann B., Laier C., Pawlikowski M., Brand M. Among three different executive functions, general executive control ability is a key predictor of decision making under objective risk. Front Psychol 2014, 5.
49. Dong G., Hu Y., Lin X., Lu Q. What makes Internet addicts continue playing online even when faced by severe negative consequences? Possible explanations from an fMRI study. Biol Psychol 2013, 94(2):282-289.
50. Dong G., DeVito E.E., Du X., Cui Z. Impaired inhibitory control in 'internet addiction disorder': a functional magnetic resonance imaging study. Psychiatry Res 2012, 203(2):153-158.
51. Dong G., Zhou H., Zhao X. Male Internet addicts show impaired executive control ability: evidence from a color-word Stroop task. Neurosci Lett 2011, 499(2):114-118.
52. Dong G., Lin X., Potenza M.N. Decreased functional connectivity in an executive control network is related to impaired executive function in Internet gaming disorder. Prog neuropsychopharmacol Biol Psychiatry 2015, 57:76-85.
53. Hester R., Lubman D.I., Yücel M. The role of executive control in human drug addiction. Behavioral Neuroscience of Drug Addiction 2010, 301-318. Springer.
54. Dong G., Hu Y., Lin X. Reward/punishment sensitivities among internet addicts: implications for their addictive behaviors. Prog neuropsychopharmacol Biol Psychiatry 2013, 46:139-145.
55. Everitt B.J., Hutcheson D.M., Ersche K.D., Pelloux Y., Dalley J.W., Robbins T.W. The orbital prefrontal cortex and drug addiction in laboratory animals and humans. Ann N Y Acad Sci 2007, 1121(1):576-597.
56. Goldstein R.Z., Volkow N.D. Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nat Rev Neurosci 2011, 12(11):652-669.
57. Sofuoglu M., DeVito E.E., Waters A.J., Carroll K.M. Cognitive enhancement as a treatment for drug addictions. Neuropharmacology 2013, 64:452-463.
58. Dong G., Lin X., Zhou H., Lu Q. Cognitive flexibility in Internet addicts: fMRI evidence from difficult-to-easy and easy-to-difficult switching situations. Addict Behav 2014, 39(3):677-683.
59. Dong G., Huang J., Du X. Enhanced reward sensitivity and decreased loss sensitivity in Internet addicts: an fMRI study during a guessing task. J Psychiatric Res 2011, 45(11):1525-1529.