Neural Mechanisms of the Reward System and the Cognitive Control System in Internet Addicts
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Published
Mar 29, 2023
Abstract
As a behavioral addiction, Internet addiction has become a global problem that seriously affects people’s mental health. According to the neurobiological model of brain development, revealing the neural mechanisms of reward and the cognitive control system of Internet addicts is the key to solving internet addiction. The key to the problem of addiction is also a major issue in psychological research. Behavioral research has explored the characteristics of high reward seeking and low cognitive control in Internet addiction; research on neural mechanisms has revealed that the deficits in reward and cognitive control systems are the root of this behavior. Comparative studies with drug addiction have found that Internet addiction has a unique reward mechanism. These studies have deepened the understanding of the psychological and neural mechanisms of Internet addiction, but there are still differences in the screening and inclusion criteria for Internet addiction. There are some problems that need to be solved urgently, such as science, general classification, lack of causal research, controversial intervention and treatment effects, and loopholes in research paradigms.
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Keywords
Internet, Addiction, Adolescent, Reward Seeking, Cognitive Control, Neural Mechanism
References
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22. Kim HS, Hodgins DC. Component model of addiction treatment: A pragmatic transdiagnostic treatment model of behavioral and substance addictions. Front Psychiatry 2018; 9:406. DOI: https://doi.org/10.3389/fpsyt.2018.00406
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27. Hou H, Jia S, Hu S, Fan R, Sun W, Sun T, Zhang H. Reduced striatal dopamine transporters in people with internet addiction disorder. J Biomed Biotechnol 2012; 2012:854524. DOI: https://doi.org/10.1155/2012/854524
28. Zhou Y, Lin FC, Du YS, Qin LD, Zhao ZM, Xu JR, Lei H. Gray matter abnormalities in Internet addiction: A voxel-based morphometry study. Eur J Radiol 2011; 79(1):92-95. DOI: https://doi.org/10.1016/j.ejrad.2009.10.025
29. Wang Y, Zou Z, Song H, Xu X, Wang H, d’Oleire Uquillas F, Huang X. Altered gray matter volume and white matter integrity in college students with mobile phone dependence. Front Psychol 2016; 7:597. DOI: https://doi.org/10.3389/fpsyg.2016.00597
30. Qin K, Zhang F, Chen T, Li L, Li W, Suo X, Lei D, Kemp GJ, Gong Q. Shared gray matter alterations in individuals with diverse behavioral addictions: A voxel-wise meta-analysis. J Behav Addict 2020; 9(1):44-57. DOI: https://doi.org/10.1556/2006.2020.00006
31. Koepp MJ, Gunn RN, Lawrence AD, Cunningham VJ, Dagher A, Jones T, Brooks DJ, Bench CJ, Grasby PM. Evidence for striatal dopamine release during a video game. Nature 1998; 393(6682):266-268. DOI: https://doi.org/10.1038/30498
32. Trifilieff P, Martinez D. Imaging addiction: D2 receptors and dopamine signaling in the striatum as biomarkers for impulsivity. Neuropharmacology 2014; 76(Pt B):498-509. DOI: https://doi.org/10.1016/j.neuropharm.2013.06.031
33. Gilman JM, Lee S, Kuster JK, Lee MJ, Kim BW, van der Kouwe A, Blood AJ, Breiter HC. Variable activation in striatal subregions across components of a social influence task in young adult cannabis users. Brain Behav 2016; 6(5):e00459. DOI: https://doi.org/10.1002/brb3.459
34. Richlan F, Schubert J, Mayer R, Hutzler F, Kronbichler M. Action video gaming and the brain: fMRI effects without behavioral effects in visual and verbal cognitive tasks. Brain Behav 2017; 8(1):e00877. DOI: https://doi.org/10.1002/brb3.877
35. Wang L, Yang G, Zheng Y, Li Z, Qi Y, Li Q, Liu X. Enhanced neural responses in specific phases of reward processing in individuals with Internet gaming disorder. J Behav Addict. 2021; 10(1):99-111. DOI: https://doi.org/10.1556/2006.2021.00003
36. Liu J, Gao XP, Osunde I, Li X, Zhou SK, Zheng HR, Li LJ. Increased regional homogeneity in internet addiction disorder: A resting state functional magnetic resonance imaging study. Chin Med J (Engl) 2010; 123(14):1904-1908.
37. Patel SH, Azzam PN. Characterization of N200 and P300: Selected studies of the Event-Related Potential. Int J Med Sci 2005; 2(4):147-154. DOI: https://doi.org/10.7150/ijms.2.147
38. Dong G, Devito EE, Du X, Cui Z. Impaired inhibitory control in ‘internet addiction disorder’: a functional magnetic resonance imaging study. Psychiatry Res 2012; 203(2-3):153-158. DOI: https://doi.org/10.1016/j.pscychresns.2012.02.001
39. Pilli R, Naidu M, Pingali UR, Shobha JC, Reddy AP. A computerized stroop test for the evaluation of psychotropic drugs in healthy participants. Indian J Psychol Med 2013; 35(2):180-189. DOI: https://doi.org/10.4103/0253-7176.116251
40. Parris BA. Task conflict in the Stroop task: When Stroop interference decreases as Stroop facilitation increases in a low task conflict context. Front Psychol 2014; 5:1182. DOI: https://doi.org/10.3389/fpsyg.2014.01182
41. Pavarini SCI, Brigola AG, Luchesi BM, Souza ÉN, Rossetti ES, Fraga FJ, Guarisco LPC, Terassi M, Oliveira NA, Hortense P, Pedroso RV, Ottaviani AC. On the use of the P300 as a tool for cognitive processing assessment in healthy aging: A review. Dement Neuropsychol 2018; 12(1):1-11. DOI: https://doi.org/10.1590/1980-57642018dn12-010001
42. Park B, Han DH, Roh S. Neurobiological findings related to Internet use disorders. Psychiatry Clin Neurosci 2017; 71(7):467-478. DOI: https://doi.org/10.1111/pcn.12422
43. Chen H, Dong G, Li K. Overview on brain function enhancement of Internet addicts through exercise intervention: Based on reward-execution-decision cycle. Front Psychiatry 2023; 14:1094583. DOI: https://doi.org/10.3389/fpsyt.2023.1094583
44. Lin F, Zhou Y, Du Y, Qin L, Zhao Z, Xu J, Lei H. Abnormal white matter integrity in adolescents with internet addiction disorder: A tract-based spatial statistics study. PLoS One 2012; 7(1):e30253. DOI: https://doi.org/10.1371/journal.pone.0030253
45. Łukawski K, Rusek M, Czuczwar SJ. Can pharmacotherapy play a role in treating internet addiction disorder? Expert Opin Pharmacother 2019; 20(11):1299-1301. DOI: https://doi.org/10.1080/14656566.2019.1612366
46. Tereshchenko S, Kasparov E. Neurobiological risk factors for the development of internet addiction in adolescents. Behav Sci (Basel) 2019; 9(6):62. DOI: https://doi.org/10.3390/bs906006
47. Hammond CJ, Mayes LC, Potenza MN. Neurobiology of adolescent substance use and addictive behaviors: Treatment implications. Adolesc Med State Art Rev 2014; 25(1):15-32.
2. Young KS. Internet addiction: The emergence of a new clinical disorder. CyberPsychol Behav 1998; 1(3):237-244. DOI: https://doi.org/10.1089/cpb.1998.1.237
3. Jorgenson AG, Hsiao RC, Yen CF. Internet addiction and other behavioral addictions. Child Adolesc Psychiatr Clin N Am 2016; 25(3):509-520. DOI: https://doi.org/10.1016/j.chc.2016.03.004
4. Panova T, Carbonell X. Is smartphone addiction really an addiction? J Behav Addict 2018; 7(2):252-259. DOI: https://doi.org/10.1556/2006.7.2018.49
5. Shaw M, Black DW. Internet addiction: Definition, assessment, epidemiology and clinical management. CNS Drugs 2008; 22(5):353-365. DOI: https://doi.org/10.2165/00023210-200822050-00001
6. Grant JE, Potenza MN, Weinstein A, Gorelick DA. Introduction to behavioral addictions. Am J Drug Alcohol Abuse 2010; 36(5):233-241. DOI: https://doi.org/10.3109/00952990.2010.491884
7. Baroni S, Marazziti D, Mucci F, Diadema E, Dell’Osso L. Problematic Internet use in drug addicts under treatment in public rehab centers. World J Psychiatry 2019; 9(3):55-64. DOI: https://doi.org/10.5498/wjp.v9.i3.55
8. Besser B, Loerbroks L, Bischof G, Bischof A, Rumpf HJ. Performance of the DSM-5-based criteria for Internet addiction: A factor analytical examination of three samples. J Behav Addict 2019; 8(2):288-294. DOI: https://doi.org/10.1556/2006.8.2019.19
9. Cash H, Rae CD, Steel AH, Winkler A. Internet addiction: A brief summary of research and practice. Curr Psychiatry Rev 2012; 8(4):292-298. DOI: https://doi.org/10.2174/157340012803520513
10. Yu M, Liu T, Shangguan F, Sui J, Shi J. The neurodevelopment of delay discounting for monetary rewards in pre-adolescent children. Sci Rep 2021; 11(1):8337. DOI: https://doi.org/10.1038/s41598-021-87282-z
11. Institute of Medicine (US) and National Research Council (US) Committee on the Science of Adolescence. The science of adolescent risk-taking: Workshop report. Washington (DC): National Academies Press (US); 2011. 3, Biobehavioral Processes. Available from: https://www.ncbi.nlm.nih.gov/books/NBK53414/
12. Meerkerk GJ, Van Den Eijnden RJ, Vermulst AA, Garretsen HF. The Compulsive Internet Use Scale (CIUS): Some psychometric properties. Cyberpsychol Behav 2009; 12(1):1-6. DOI: https://doi.org/10.1089/cpb.2008.0181
13. Ko CH, Yen JY, Chen CC, Chen SH, Wu K, Yen CF. Tridimensional personality of adolescents with internet addiction and substance use experience. Can J Psychiatry 2006; 51(14):887-894. DOI: https://doi.org/10.1177/070674370605101404
14. Hu C, Kumar S, Huang J, Ratnavelu K. Disinhibition of negative true self for identity reconstructions in cyberspace: Advancing self-discrepancy theory for virtual setting. PLoS One 2017; 12(4):e0175623. DOI: https://doi.org/10.1371/journal.pone.0175623
15. Gabarnet A, Montesano A, Feixas G. Virtual-self Identity Construal in Online Video Games: A Repertory Grid Study Protocol. Aloma: Revista de Psicologia, Ciències de l’Educació i de l’Esport 2022; 40:9-21. DOI: https://doi.org/10.51698/aloma.2022.40.1.9-21
16. Brand M, Young KS, Laier C. Prefrontal control and internet addiction: A theoretical model and review of neuropsychological and neuroimaging findings. Front Hum Neurosci 2014; 8:375. DOI: https://doi.org/10.3389/fnhum.2014.00375
17. Xu P, Wu D, Chen Y, Wang Z, Xiao W. The effect of response inhibition training on risky decision-making task performance. Front Psychol 2020; 11:1806. DOI: https://doi.org/10.3389/fpsyg.2020.01806
18. Zhang Y, Mei S, Li L, Chai J, Li J, Du H. The relationship between impulsivity and internet addiction in Chinese college students: A moderated mediation analysis of meaning in life and self-esteem. PLoS One 2015; 10(7):e0131597. DOI: https://doi.org/10.1371/journal.pone.0131597
19. Van Rooij AJ, Prause N. A critical review of “Internet addiction” criteria with suggestions for the future. J Behav Addict 2014; 3(4):203-213. DOI: https://doi.org/10.1556/JBA.3.2014.4.1
20. Gardner EL. Addiction and brain reward and antireward pathways. Adv Psychosom Med 2011; 30:22-60. DOI: https://doi.org/10.1159/000324065
21. Friedman NP, Robbins TW. The role of prefrontal cortex in cognitive control and executive function. Neuropsychopharmacology. 2022; 47(1):72-89. DOI: https://doi.org/10.1038/s41386-021-01132-0
22. Kim HS, Hodgins DC. Component model of addiction treatment: A pragmatic transdiagnostic treatment model of behavioral and substance addictions. Front Psychiatry 2018; 9:406. DOI: https://doi.org/10.3389/fpsyt.2018.00406
23. Haber SN, Knutson B. The reward circuit: Linking primate anatomy and human imaging. Neuropsychopharmacology 2010; 35(1):4-26. DOI: https://doi.org/10.1038/npp.2009.129
24. Blum K, Bowirrat A, Braverman ER, Baron D, Cadet JL, Kazmi S, Elman I, Thanos PK, Badgaiyan RD, Downs WB, Bagchi D, Llanos-Gomez L, Gold MS. Reward Deficiency Syndrome (RDS): A cytoarchitectural common neurobiological trait of all addictions. Int J Environ Res Public Health 2021; 18(21):11529. DOI: https://doi.org/10.3390/ijerph182111529
25. Blum K, Chen AL, Oscar-Berman M, Chen TJ, Lubar J, White N, Lubar J, Bowirrat A, Braverman E, Schoolfield J, Waite RL, Downs BW, Madigan M, Comings DE, Davis C, Kerner MM, Knopf J, Palomo T, Giordano JJ, Morse SA, Fornari F, Barh D, Femino J, Bailey JA. Generational association studies of dopaminergic genes in reward deficiency syndrome (RDS) subjects: Selecting appropriate phenotypes for reward dependence behaviors. Int J Environ Res Public Health 2011; 8(12):4425-4459. DOI: https://doi.org/10.3390/ijerph8124425
26. Cerniglia L, Cimino S, Marzilli E, Pascale E, Tambelli R. Associations among internet addiction, genetic polymorphisms, family functioning, and psychopathological risk: Cross-sectional exploratory study. JMIR Ment Health 2020; 7(12):e17341. DOI: https://doi.org/10.2196/17341
27. Hou H, Jia S, Hu S, Fan R, Sun W, Sun T, Zhang H. Reduced striatal dopamine transporters in people with internet addiction disorder. J Biomed Biotechnol 2012; 2012:854524. DOI: https://doi.org/10.1155/2012/854524
28. Zhou Y, Lin FC, Du YS, Qin LD, Zhao ZM, Xu JR, Lei H. Gray matter abnormalities in Internet addiction: A voxel-based morphometry study. Eur J Radiol 2011; 79(1):92-95. DOI: https://doi.org/10.1016/j.ejrad.2009.10.025
29. Wang Y, Zou Z, Song H, Xu X, Wang H, d’Oleire Uquillas F, Huang X. Altered gray matter volume and white matter integrity in college students with mobile phone dependence. Front Psychol 2016; 7:597. DOI: https://doi.org/10.3389/fpsyg.2016.00597
30. Qin K, Zhang F, Chen T, Li L, Li W, Suo X, Lei D, Kemp GJ, Gong Q. Shared gray matter alterations in individuals with diverse behavioral addictions: A voxel-wise meta-analysis. J Behav Addict 2020; 9(1):44-57. DOI: https://doi.org/10.1556/2006.2020.00006
31. Koepp MJ, Gunn RN, Lawrence AD, Cunningham VJ, Dagher A, Jones T, Brooks DJ, Bench CJ, Grasby PM. Evidence for striatal dopamine release during a video game. Nature 1998; 393(6682):266-268. DOI: https://doi.org/10.1038/30498
32. Trifilieff P, Martinez D. Imaging addiction: D2 receptors and dopamine signaling in the striatum as biomarkers for impulsivity. Neuropharmacology 2014; 76(Pt B):498-509. DOI: https://doi.org/10.1016/j.neuropharm.2013.06.031
33. Gilman JM, Lee S, Kuster JK, Lee MJ, Kim BW, van der Kouwe A, Blood AJ, Breiter HC. Variable activation in striatal subregions across components of a social influence task in young adult cannabis users. Brain Behav 2016; 6(5):e00459. DOI: https://doi.org/10.1002/brb3.459
34. Richlan F, Schubert J, Mayer R, Hutzler F, Kronbichler M. Action video gaming and the brain: fMRI effects without behavioral effects in visual and verbal cognitive tasks. Brain Behav 2017; 8(1):e00877. DOI: https://doi.org/10.1002/brb3.877
35. Wang L, Yang G, Zheng Y, Li Z, Qi Y, Li Q, Liu X. Enhanced neural responses in specific phases of reward processing in individuals with Internet gaming disorder. J Behav Addict. 2021; 10(1):99-111. DOI: https://doi.org/10.1556/2006.2021.00003
36. Liu J, Gao XP, Osunde I, Li X, Zhou SK, Zheng HR, Li LJ. Increased regional homogeneity in internet addiction disorder: A resting state functional magnetic resonance imaging study. Chin Med J (Engl) 2010; 123(14):1904-1908.
37. Patel SH, Azzam PN. Characterization of N200 and P300: Selected studies of the Event-Related Potential. Int J Med Sci 2005; 2(4):147-154. DOI: https://doi.org/10.7150/ijms.2.147
38. Dong G, Devito EE, Du X, Cui Z. Impaired inhibitory control in ‘internet addiction disorder’: a functional magnetic resonance imaging study. Psychiatry Res 2012; 203(2-3):153-158. DOI: https://doi.org/10.1016/j.pscychresns.2012.02.001
39. Pilli R, Naidu M, Pingali UR, Shobha JC, Reddy AP. A computerized stroop test for the evaluation of psychotropic drugs in healthy participants. Indian J Psychol Med 2013; 35(2):180-189. DOI: https://doi.org/10.4103/0253-7176.116251
40. Parris BA. Task conflict in the Stroop task: When Stroop interference decreases as Stroop facilitation increases in a low task conflict context. Front Psychol 2014; 5:1182. DOI: https://doi.org/10.3389/fpsyg.2014.01182
41. Pavarini SCI, Brigola AG, Luchesi BM, Souza ÉN, Rossetti ES, Fraga FJ, Guarisco LPC, Terassi M, Oliveira NA, Hortense P, Pedroso RV, Ottaviani AC. On the use of the P300 as a tool for cognitive processing assessment in healthy aging: A review. Dement Neuropsychol 2018; 12(1):1-11. DOI: https://doi.org/10.1590/1980-57642018dn12-010001
42. Park B, Han DH, Roh S. Neurobiological findings related to Internet use disorders. Psychiatry Clin Neurosci 2017; 71(7):467-478. DOI: https://doi.org/10.1111/pcn.12422
43. Chen H, Dong G, Li K. Overview on brain function enhancement of Internet addicts through exercise intervention: Based on reward-execution-decision cycle. Front Psychiatry 2023; 14:1094583. DOI: https://doi.org/10.3389/fpsyt.2023.1094583
44. Lin F, Zhou Y, Du Y, Qin L, Zhao Z, Xu J, Lei H. Abnormal white matter integrity in adolescents with internet addiction disorder: A tract-based spatial statistics study. PLoS One 2012; 7(1):e30253. DOI: https://doi.org/10.1371/journal.pone.0030253
45. Łukawski K, Rusek M, Czuczwar SJ. Can pharmacotherapy play a role in treating internet addiction disorder? Expert Opin Pharmacother 2019; 20(11):1299-1301. DOI: https://doi.org/10.1080/14656566.2019.1612366
46. Tereshchenko S, Kasparov E. Neurobiological risk factors for the development of internet addiction in adolescents. Behav Sci (Basel) 2019; 9(6):62. DOI: https://doi.org/10.3390/bs906006
47. Hammond CJ, Mayes LC, Potenza MN. Neurobiology of adolescent substance use and addictive behaviors: Treatment implications. Adolesc Med State Art Rev 2014; 25(1):15-32.
How to Cite
Dossi, N., & Pesce, R. C. (2023). Neural Mechanisms of the Reward System and the Cognitive Control System in Internet Addicts. Science Insights, 42(3), 867–875. https://doi.org/10.15354/si.23.re255
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Review
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