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Altered Functional Disconnectivity in Internet Addicts with Resting-State Functional Magnetic Resonance Imaging
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 Title & Authors
Altered Functional Disconnectivity in Internet Addicts with Resting-State Functional Magnetic Resonance Imaging
Seok, Ji-Woo; Sohn, Jin-Hun;
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 Abstract
Objective: In this study, we used resting-state fMRI data to map differences in functional connectivity between a comprehensive set of 8 distinct cortical and subcortical brain regions in healthy controls and Internet addicts. We also investigated the relationship between resting state connectivity strength and the level of psychopathology (ex. score of internet addiction scale and score of Barratt impulsiveness scale). Background: There is a lot of evidence of relationship between Internet addiction and impaired inhibitory control. Clinical evidence suggests that Internet addicts have a high level of impulsivity as measured by behavioral task of response inhibition and a self report questionnaire. Method: 15 Internet addicts and 15 demographically similar non-addicts participated in the current resting-state fMRI experiment. For the connectivity analysis, regions of interests (ROIs) were defined based on the previous studies of addictions. Functional connectivity assessment for each subject was obtained by correlating time-series across the ROIs, resulting in matrixs for each subject. Within-group, functional connectivity patterns were observed by entering the z maps of the ROIs of each subject into second-level one sample t test. Two sample t test was also performed to examine between group differences. Results: Between group, the analysis revealed that the connectivity in between the orbito frontal cortex and inferior parietal cortex, between orbito frontal cortex and putamen, between the orbito frontal cortex and anterior cingulate cortex, between the insula and anterior cingulate cortex, and between amydgala and insula was significantly stronger in control group than in the Internet addicts, while the connectivity in between the orbito frontal cortex and insula showed stronger negative correlation in the Internet addicts relative to control group (p < 0.001, uncorrected). No significant relationship between functional connectivity strength and current degree of Internet addiction and degree of impulsitivy was seen. Conclusion: This study found that Internet addicts had declined connectivity strength in the orbitofrontal cortex (OFC) and other regions (e.g., ACC, IPC, and insula) during resting-state. It may reflect deficits in the OFC function to process information from different area in the corticostriatal reward network. Application: The results might help to develop theoretical modeling of Internet addiction for Internet addiction discrimination.
 Keywords
Internet addiction;Inhibitory control;Resting-state fMRI;Functional connectivity;Orbitofrontal cortex;
 Language
English
 Cited by
 References
1.
Association, A.P., DSM 5 American Psychiatric Association, 2013.

2.
Birbaumer, N., Veit, R., Lotze, M., Erb, M., Hermann, C., Grodd, W. and Flor, H., Deficient fear conditioning in psychopathy: a functional magnetic resonance imaging study', Archives of general psychiatry, 62(7), 799-805, 2005. crossref(new window)

3.
Cao, F.l. and Su, L.Y., Internet addiction among Chinese adolescents: prevalence and psychological features', Child: care, health and development, 33(3), 275-281, 2007. crossref(new window)

4.
Cavedini, P., Riboldi, G., Keller, R., D'Annucci, A. and Bellodi, L., Frontal lobe dysfunction in pathological gambling patients', Biological psychiatry, 51(4), 334-341, 2002. crossref(new window)

5.
Dong, G., DeVito, E.E., Du, X. and Cui, Z., Impaired inhibitory control in internet addiction disorder': A functional magnetic resonance imaging study', Psychiatry Research: Neuroimaging, 203(2), 153-158, 2012. crossref(new window)

6.
Dong, G., Lu, Q., Zhou, H. and Zhao, X., Impulse inhibition in people with Internet addiction disorder: electrophysiological evidence from a Go/NoGo study', Neuroscience letters, 485(2), 138-142, 2010. crossref(new window)

7.
Dong, G., Lu, Q., Zhou, H. and Zhao, X., Precursor or sequela: pathological disorders in people with Internet addiction disorder', PloS one, 6(2), e14703, 2011. crossref(new window)

8.
Fox, M.D., Zhang, D., Snyder, A.Z. and Raichle, M.E., The global signal and observed anticorrelated resting state brain networks', Journal of neurophysiology, 101(6), 3270-3283, 2009. crossref(new window)

9.
Kim, H.S., Internet Addiction Nanum Press, 2000.

10.
Kim, J.H., Lau, C., Cheuk, K.-K., Kan, P., Hui, H.L. and Griffiths, S.M., Brief report: Predictors of heavy Internet use and associations with health-promoting and health risk behaviors among Hong Kong university students', Journal of adolescence, 33(1), 215-220, 2010. crossref(new window)

11.
Ko, C.H., Hsiao, S., Liu, G.-C., Yen, J.-Y., Yang, M.-J. and Yen, C.-F., The characteristics of decision making, potential to take risks, and personality of college students with Internet addiction', Psychiatry research, 175(1), 121-125, 2010. crossref(new window)

12.
Lee, H.S., Impulsivity test Korea Guidance, 2002.

13.
Lee, M.S., Oh, E.Y., Cho, S.M., Hong, M.J. and Moon, J.S., An assessment of adolescent Internet addiction problems related to depression, social anxiety and peer relationship', Journal of Korean Neuropsychiatric Association, 40(4), 616-628, 2001.

14.
Promotion, K.A.f.D.O.a., The development study of Internet addiction to prevent program and K-scale Korea Agency for Digital Opportunity and Promotion Press, 2002.

15.
Raichle, M.E. and Mintun, M.A., Brain work and brain imaging', Annu. Rev. Neurosci., 29, 449-476, 2006. crossref(new window)

16.
Shaw, M. and Black, D.W., Internet addiction', CNS drugs, 22(5), 353-365, 2008. crossref(new window)

17.
Shulman, R.G., Rothman, D.L., Behar, K.L. and Hyder, F., Energetic basis of brain activity: implications for neuroimaging', Trends in neurosciences, 27(8), 489-495, 2004. crossref(new window)

18.
Spectr, C., Prevalence underestimated in problematic Internet use study', CNS Spectr, 12, 14-15, 2006.

19.
Volkow, N.D., Fowler, J.S., Wang, G.-J. and Goldstein, R.Z., Role of dopamine, the frontal cortex and memory circuits in drug addiction: insight from imaging studies', Neurobiology of learning and memory, 78(3), 610-624, 2002. crossref(new window)

20.
Young, K.S., Caught in the net: How to recognize the signs of internet addiction--and a winning strategy for recovery John Wiley & Sons, 1998.