Altered Functional Connectivity of the Nucleus Accumbens and Amygdala in Cyber Addiction: A Resting State Functional Magnetic Resonance Imaging Study
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Objective: Cyber addiction, which is more vulnerable in adolescents, is defined as the excessive use of computers and the Internet that causes serious psychological, social, and physical problems. In this study, we investigated the resting-state functional connectivity (rsFC) in adolescents with cyber addiction. Methods: We collected and analyzed resting-state functional neuroimaging data of 20 patients with cyber addiction, aged 13−18 years, and 27 healthy controls. Based on previous studies, the seed regions included the dorsolateral prefrontal cortex, medial orbitofrontal cortex, lateral orbitofrontal cortex, dorsal anterior cingulate cortex, insula, hippocampus, amygdala, nucleus accumbens, and the ventral tegmental area. Seed-to-voxel analyses were performed to investigate the differences between patients and healthy controls. A correlation analysis between rsFC and cyber addiction severity was also performed. Results: Patients with cyber addiction showed the following characteristics: increased positive rsFC between the left insular−right middle temporal gyrus; increased positive rsFC between the right hippocampus−right precentral gyrus; increased positive rsFC between the right amygdala−right precentral gyrus and right parietal operculum cortex; increased negative rsFC between the left nucleus accumbens−right cerebellum crus II and right cerebellum VI. Conclusion: Adolescents with cyber addiction show altered functional connectivity during the resting state. The findings of this study may help us better understand the neuropathology of cyber addiction in adolescents.
Abstract
Objective: Cyber addiction, which is more vulnerable in adolescents, is defined as the excessive use of computers and the Internet that causes serious psychological, social, and physical problems. In this study, we investigated the resting-state functional connectivity (rsFC) in adolescents with cyber addiction. Methods: We collected and analyzed resting-state functional neuroimaging data of 20 patients with cyber addiction, aged 13−18 years, and 27 healthy controls. Based on previous studies, the seed regions included the dorsolateral prefrontal cortex, medial orbitofrontal cortex, lateral orbitofrontal cortex, dorsal anterior cingulate cortex, insula, hippocampus, amygdala, nucleus accumbens, and the ventral tegmental area. Seed-to-voxel analyses were performed to investigate the differences between patients and healthy controls. A correlation analysis between rsFC and cyber addiction severity was also performed. Results: Patients with cyber addiction showed the following characteristics: increased positive rsFC between the left insular−right middle temporal gyrus; increased positive rsFC between the right hippocampus−right precentral gyrus; increased positive rsFC between the right amygdala−right precentral gyrus and right parietal operculum cortex; increased negative rsFC between the left nucleus accumbens−right cerebellum crus II and right cerebellum VI. Conclusion: Adolescents with cyber addiction show altered functional connectivity during the resting state. The findings of this study may help us better understand the neuropathology of cyber addiction in adolescents.
참고문헌 (51)
- Ali Khaleghi, "Computational Neuroscience Approach to Psychiatry: A Review on Theory-driven Approaches", Clinical Psychopharmacology and Neuroscience, 20(1), pp.26~36 (2022), 대한정신약물학회[DOI]
- Sang Won Lee, "Alterations of Power Spectral Density in Salience Network during Thought-action Fusion Induction Paradigm in Obsessive-compulsive Disorder", Clinical Psychopharmacology and Neuroscience, 20(3), pp.415~426 (2022), 대한정신약물학회[DOI]
- Young-Eun Oh, "Impact of Social Defeat Stress on DNA Methylation in Drd2, Nr3c1, and Stmn1 in Wild-type and Stmn1 Knock-out Mice", Clinical Psychopharmacology and Neuroscience, 20(1), pp.51~60 (2022), 대한정신약물학회[DOI]
- Ernst M, "Triadic model of the neurobiology of motivated behavior in adolescence", Psychol Med, 36, pp.299~312 (2006)
- Pine DS, "Emotional reactivity and risk for psychopathology among adolescents", CNS Spectr, 6, pp.27~35 (2001)
- Saville BK, "Internet addiction and delay discounting in college students", Psychol Rec, 60, pp.273~286 (2010)
- Kim YJ, "The cognitive dysregulation of Internet addiction and its neurobiological correlates", Front Biosci(Elite Ed), 9, pp.307~320 (2017)
- Ko CH, "Brain activities associated with gaming urge of online gaming addiction", J Psychiatr Res, 43, pp.739~747 (2009)
- Dong G, "What makes Internet addicts continue playing online even when faced by severe negative consequences? Possible explanations from an fMRI study", Biol Psychol, 94, pp.282~289 (2013)
- Cheng H, "Alterations in amygdala connectivity in internet addiction disorder", Sci Rep, 10, pp.2370~ (2020)
- Dong G, "Alterations in regional homogeneity of resting-state brain activity in internet gaming addicts", Behav Brain Funct, 8, pp.41~ (2012)
- Dong G, "Decreased functional connectivity in an executive control network is related to impaired executive function in Internet gaming disorder", Prog Neuropsychopharmacol Biol Psychiatry, 57, pp.76~85 (2015)
- Kim H, "Resting-state regional homogeneity as a biological marker for patients with Internet gaming disorder : a comparison with patients with alcohol use disorder and healthy controls", Prog Neuropsychopharmacol Biol Psychiatry, 60, pp.104~111 (2015)
- Zhang JT, "Altered resting-state functional connectivity of the insula in young adults with Internet gaming disorder", Addict Biol, 21, pp.743~751 (2016)
- American Psychiatric Association, "Diagnostic and statistical manual of mental disorders: DSM-5" (2013), American Psychiatric Association
- Young K, "Internet addiction : the emergence of a new clinical disorder", CyberPsychol Behav, 1, pp.237~244 (1998)
- Third standardization of Korean internet addiction proneness scale, "Sin G", National Information Society Agency, ~, pp.NIA IV-RER-11050 (2011)
- A study of the development of internet game addiction scale for children and adolescents, "Kim B", National Information Society Agency, ~ (2006)
- Kim D, "Development of Korean Smartphone addiction proneness scale for youth", PLoS One, 9, pp.e97920~ (2014)
- 김영신, "The Reliability and Validity of Kiddie-Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version-Korean Version (K-SADS-PL-K)", Yonsei Medical Journal, 45(1), pp.81~89 (2004), 연세대학교의과대학
- Whitfield-Gabrieli S, "Conn : a functional connectivity toolbox for correlated and anticorrelated brain networks", Brain Connect, 2, pp.125~141 (2012)
- Martz ME, "Frontostriatal resting state functional connectivity in resilient and non-resilient adolescents with a family history of alcohol use disorder", J Child Adolesc Psychopharmacol, 29, pp.508~515 (2019)
- Ma N, "Addiction related alteration in resting-state brain connectivity", Neuroimage, 49, pp.738~744 (2010)
- Zhou Y, "Functional connectivity of the caudal anterior cingulate cortex is decreased in autism", PLoS One, 11, pp.e0151879~ (2016)
- Chen CY, "Altered functional connectivity of the insula and nucleus accumbens in internet gaming disorder : a resting state fMRI study", Eur Addict Res, 22, pp.192~200 (2016)
- Tahmasian M, "Aberrant intrinsic connectivity of hippocampus and amygdala overlap in the fronto-insular and dorsomedial-prefrontal cortex in major depressive disorder", Front Hum Neurosci, 7, pp.639~ (2013)
- Anand A, "Reciprocal effects of antidepressant treatment on activity and connectivity of the mood regulating circuit : an FMRI study", J Neuropsychiatry Clin Neurosci, 19, pp.274~282 (2007)
- Ballard IC, "Dorsolateral prefrontal cortex drives mesolimbic dopaminergic regions to initiate motivated behavior", J Neurosci, 31, pp.10340~10346 (2011)
- Woo CW, "Cluster-extent based thresholding in fMRI analyses : pitfalls and recommendations", Neuroimage, 91, pp.412~419 (2014)
- Koob GF, "Neurocircuitry of addiction", Neuropsychopharmacology, 35, pp.217~238 (2010)
- Limbrick-Oldfield EH, "Neural substrates of cue reactivity and craving in gambling disorder", Transl Psychiatry, 7, pp.e992~ (2017)
- de Greck M, "Decreased neuronal activity in reward circuitry of pathological gamblers during processing of personal relevant stimuli", Hum Brain Mapp, 31, pp.1802~1812 (2010)
- van Holst RJ, "Striatal connectivity changes following gambling wins and near-misses : associations with gambling severity", Neuroimage Clin, 5, pp.232~239 (2014)
- Kühn S, "Brains online : structural and functional correlates of habitual Internet use", Addict Biol, 20, pp.415~422 (2015)
- Barrós-Loscertales A, "Reduced striatal volume in cocaine-dependent patients", Neuroimage, 56, pp.1021~1026 (2011)
- Chanraud S, "Brain morphometry and cognitive performance in detoxified alcohol-dependents with preserved psychosocial functioning", Neuropsychopharmacology, 32, pp.429~438 (2007)
- Moulton EA, "The cerebellum and addiction : insights gained from neuroimaging research", Addict Biol, 19, pp.317~331 (2014)
- Yoon EJ, "Altered hippocampal volume and functional connectivity in males with Internet gaming disorder comparing to those with alcohol use disorder", Sci Rep, 7, pp.5744~ (2017)
- Cooke DF, "Sensorimotor integration in the precentral gyrus : polysensory neurons and defensive movements", J Neurophysiol, 91, pp.1648~1660 (2004)
- Ding WN, "Trait impulsivity and impaired prefrontal impulse inhibition function in adolescents with internet gaming addiction revealed by a Go", No-Go fMRI study, 2014, pp.10, 20~
- Schmitgen MM, "Neural correlates of cue reactivity in individuals with smartphone addiction", Addict Behav, 108, pp.106422~ (2020)
- "The neural features in the precentral gyrus predict the severity of internet game disorder: results from the multi-voxel pattern analyses" (2020)[URL]
- Droutman V, "Revisiting the role of the insula in addiction", Trends Cogn Sci, 19, pp.414~420 (2015)
- Li X, "The Iowa Gambling Task in fMRI images", Hum Brain Mapp, 31, pp.410~423 (2010)
- Lu H, "Neuroanatomical correlates of trait gambling-related cognitive distortions", J Integr Neurosci, 18, pp.231~236 (2019)
- Xu J, "Tractographybased parcellation of the human middle temporal gyrus", Sci Rep, 5, pp.18883~ (2015)
- Ding WN, "Altered default network resting-state functional connectivity in adolescents with Internet gaming addiction", PLoS One, 8, pp.e59902~ (2013)
- Yuan K, "Cortical thickness abnormalities in late adolescence with online gaming addiction", PLoS One, 8, pp.e53055~ (2013)
- Carli V, "The association between pathological internet use and comorbid psychopathology : a systematic review", Psychopathology, 46, pp.1~13 (2013)
- Stavropoulos V, "Associations between attention deficit hyperactivity and internet gaming disorder symptoms : is there consistency across types of symptoms, gender and countries?", Addict Behav Rep, 9, pp.100158~ (2019)
- Wartberg L, "A longitudinal study on psychosocial causes and consequences of Internet gaming disorder in adolescence", Psychol Med, 49, pp.287~294 (2019)