Advertisement

An Overview of the Neurobiology of Impulsivity in Gambling and Gaming Disorder

  • Kiran Punia
  • Iris M. BalodisEmail author
Impulse Control Disorders (D McGrath, Section Editor)
Part of the following topical collections:
  1. Topical Collection on Impulse Control Disorders

Abstract

Purpose of Review

Gambling disorder (GD) and gaming disorder (IGD), the two currently recognized behavioural addictions are characterized by high levels of impulsivity. Increasing research focuses on neurocognitive impulsive features in GD and IGD as these disorders can provide a “drug-free” model to study shared neural mechanisms across addictive disorders. This review provides an overview of neurobiological findings across three impulsive components of behaviour: response inhibition, delay discounting, and reward processing.

Recent Findings

Response inhibition is characterized by decreased fronto-striatal recruitment in these populations. The inclusion of emotional cues can, however, result in increased fronto-striatal responding in GD. During delay discounting, individuals with GD show steeper discounting which is associated with altered fronto-striatal representations of subjective value. Anticipatory reward processing in GD is associated with decreased ventral striatal activity, which negatively correlates with disorder severity. In IGD, evidence for enhanced reward sensitivity may be present.

Summary

Future studies are required to directly compare and contrast the neurobiological features of impulsivity across GD and IGD. Additionally, there is a strong need to incorporate longitudinal research designs to elucidate the neurobiological trajectory of these behavioural addictions. A better mechanistic understanding of impulsive features underlying substance and non-substance-based addictions, can improve prevention and treatment of addictions.

Keywords

Response inhibition Delay discounting Reward processing Addiction Anticipation Neurocognition 

Notes

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflicts of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. 1.
    Hamilton KR, Mitchell MR, Wing VC, Balodis IM, Bickel WK, Fillmore M, et al. Choice impulsivity: definitions, measurement issues, and clinical implications. Pers Disord: Theory Res Treat. 2015;6(2):182.  https://doi.org/10.1037/per0000099.CrossRefGoogle Scholar
  2. 2.
    Hamilton KR, Littlefield AK, Anastasio NC, Cunningham KA, Fink LH, Wing VC, et al. Rapid-response impulsivity: definitions, measurement issues, and clinical implications. Pers Disord: Theory Res Treat. 2015;6(2):168.  https://doi.org/10.1037/per0000100.CrossRefGoogle Scholar
  3. 3.
    Moeller FG, Barratt ES, Dougherty DM, Schmitz JM, Swann AC. Psychiatric aspects of impulsivity. Am J Psychiatry. 2001;158(11):1783–93.  https://doi.org/10.1176/appi.ajp.158.11.1783.CrossRefGoogle Scholar
  4. 4.
    Grant JE, Potenza MN, Weinstein A, Gorelick DA. Introduction to behavioral addictions. Am J Drug Alcohol Abuse 2010. 2010;36(5):233–41.  https://doi.org/10.3109/00952990.2010.491884.CrossRefGoogle Scholar
  5. 5.
    Billieux, J., Lagrange, G., Van der Linden, M., Lançon, C., Adida, M., & Jeanningros, R. (2012). Investigation of impulsivity in a sample of treatment-seeking pathological gamblers: a multidimensional perspective. Psychiatry Res 2012;198(2), 291–296.  https://doi.org/10.1016/j.psychres.2012.01.001.
  6. 6.
    Yao YW, Wang LJ, Yip SW, Chen PR, Li S, Xu J, et al. Impaired decision-making under risk is associated with gaming-specific inhibition deficits among college students with Internet gaming disorder. Psychiatry Res. 2015;229(1–2):302–9.  https://doi.org/10.1016/j.psychres.2015.07.004.CrossRefGoogle Scholar
  7. 7.
    Petry NM. Pathological gamblers, with and without substance abuse disorders, discount delayed rewards at high rates. J Abnorm Psychol. 2001;110(3):482–7.  https://doi.org/10.1037//0021-843X.110.3.482.CrossRefGoogle Scholar
  8. 8.
    • 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;56:142–8.  https://doi.org/10.1016/j.pnpbp.2014.08.016 This study examined the neural basis of probability discounting and showed alterations in risk evaluation in individuals with IGD. CrossRefGoogle Scholar
  9. 9.
    Sescousse G, Barbalat G, Domenech P, Dreher JC. Imbalance in the sensitivity to different types of rewards in pathological gambling. Brain. 2013;136(8):2527–38.  https://doi.org/10.1093/brain/awt126.CrossRefGoogle Scholar
  10. 10.
    Dong G, Lin X, Hu Y, Xie C, Du X. Imbalanced functional link between executive control network and reward network explain the online-game seeking behaviors in internet gaming disorder. Sci Rep. 2015;5:9197.  https://doi.org/10.1038/srep09197.CrossRefGoogle Scholar
  11. 11.
    Goudriaan AE, Oosterlaan J, de Beurs E, van den Brink W. Decision making in pathological gambling: a comparison between pathological gamblers, alcohol dependents, persons with Tourette syndrome, and normal controls. Cogn Brain Res. 2005;23(1):137–51.  https://doi.org/10.1016/j.cogbrainres.2005.01.017.CrossRefGoogle Scholar
  12. 12.
    • Kozak K, Lucatch AM, Lowe DJ, Balodis IM, MacKillop J, George TP. The neurobiology of impulsivity and substance use disorders: implications for treatment. Ann N Y Acad Sci. 2018.  https://doi.org/10.1111/nyas.13977 This review outlines the relationship between impulsivity and addiction, provides an overview of three neurobiological pathways that lead to impulsive behaviour, and discusses implications for treatment.
  13. 13.
    Goldstein RZ, Volkow ND. Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nat Rev Neurosci. 2011;12(11):652–69.  https://doi.org/10.1038/nrn3119.CrossRefGoogle Scholar
  14. 14.
    Goldstein RZ, Volkow ND. Drug addiction and its underlying neurobiological basis: neuroimaging evidence for the involvement of the frontal cortex. Am J Psychiatry. 2002;159(10):1642–52.  https://doi.org/10.1176/appi.ajp.159.10.1642.CrossRefGoogle Scholar
  15. 15.
    Koob GF, Le Moal M. Drug addiction, dysregulation of reward, and allostasis. Neuropsychopharmacology. 2001;24(2):97–129.  https://doi.org/10.1016/S0893-133X(00)00195-0.CrossRefGoogle Scholar
  16. 16.
    Ko CH, Liu GC, Hsiao S, Yen JY, Yang MJ, Lin WC, et al. Brain activities associated with gaming urge of online gaming addiction. J Psychiatr Res. 2009;43(7):739–47.  https://doi.org/10.1016/j.jpsychires.2008.09.012.CrossRefGoogle Scholar
  17. 17.
    Goudriaan AE, De Ruiter MB, Van Den Brink W, Oosterlaan J, Veltman DJ. Brain activation patterns associated with cue reactivity and craving in abstinent problem gamblers, heavy smokers and healthy controls: an fMRI study. Addict Biol. 2010;15(4):491–503.  https://doi.org/10.1111/j.1369-1600.2010.00242.x.CrossRefGoogle Scholar
  18. 18.
    Hariri AR, Brown SM, Williamson DE, Flory JD, de Wit H, Manuck SB. Preference for immediate over delayed rewards is associated with magnitude of ventral striatal activity. J Neurosci. 2006;26(51):13213–7.  https://doi.org/10.1523/JNEUROSCI.3446-06.2006.CrossRefGoogle Scholar
  19. 19.
    Wassum KM, Izquierdo A. The basolateral amygdala in reward learning and addiction. Neurosci Biobehav Rev. 2015;57:271–83.  https://doi.org/10.1016/j.neubiorev.2015.08.017.CrossRefGoogle Scholar
  20. 20.
    American Psychiatric Association. DSM-5®. 2013. American Psychiatric Pub.Google Scholar
  21. 21.
    World Health Organization. (2018). International statistical classification of diseases and related health problems (11th Revision). Retrieved from https://icd.who.int/browse11/l-m/en
  22. 22.
    Toce-Gerstein M, Gerstein DR. Of time and the chase: lifetime versus past-year measures of pathological gambling. J Gambl Issues. 2004;10.  https://doi.org/10.4309/jgi.2004.10.4.
  23. 23.
    Müller KW, Janikian M, Dreier M, Wölfling K, Beutel ME, Tzavara C, et al. Regular gaming behavior and internet gaming disorder in European adolescents: results from a cross-national representative survey of prevalence, predictors, and psychopathological correlates. Eur Child Adolesc Psychiatry. 2015;24(5):565–74.  https://doi.org/10.1007/s00787-014-0611-2.CrossRefGoogle Scholar
  24. 24.
    Lawrence AJ, Luty J, Bogdan NA, Sahakian BJ, Clark L. Problem gamblers share deficits in impulsive decision-making with alcohol-dependent individuals. Addiction. 2009;104(6):1006–15.  https://doi.org/10.1111/j.1360-0443.2009.02533.x.CrossRefGoogle Scholar
  25. 25.
    Choi SW, Kim H, Kim GY, Jeon Y, Park S, Lee JY, et al. Similarities and differences among Internet gaming disorder, gambling disorder and alcohol use disorder: a focus on impulsivity and compulsivity. J Behav Addict. 2014;3(4):246–53.  https://doi.org/10.1556/JBA.3.2014.4.6.CrossRefGoogle Scholar
  26. 26.
    Ledgerwood DM, Petry NM. Gambling and suicidality in treatment-seeking pathological gamblers. J Nerv Ment Dis. 2004;192(10):711–4.  https://doi.org/10.1097/01.nmd.0000142021.71880.ce.CrossRefGoogle Scholar
  27. 27.
    • Kim BS, Chang SM, Park JE, Seong SJ, Won SH, Cho MJ. Prevalence, correlates, psychiatric comorbidities, and suicidality in a community population with problematic Internet use. Psychiatry Res. 2016;244:249–56.  https://doi.org/10.1016/j.psychres.2016.07.009 This is a large epidemiological study examining problematic internet use, pathological gambling, and other mental disorders among Korean adults. CrossRefGoogle Scholar
  28. 28.
    Petry NM, Stinson FS, Grant BF. Comorbidity of DSM-IV pathological gambling and other psychiatric disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. J Clin Psychiatry. 2005;66(5):564–74.  https://doi.org/10.4088/JCP.v66n0504.CrossRefGoogle Scholar
  29. 29.
    Roberts W, Fillmore MT, Milich R. Linking impulsivity and inhibitory control using manual and oculomotor response inhibition tasks. Acta Psychol. 2011;138(3):419–28.  https://doi.org/10.1016/j.actpsy.2011.09.002.CrossRefGoogle Scholar
  30. 30.
    •• Cieslik EC, Mueller VI, Eickhoff CR, Langner R, Eickhoff SB. Three key regions for supervisory attentional control: evidence from neuroimaging meta-analyses. Neurosci Biobehav Rev. 2015;48:22–34.  https://doi.org/10.1016/j.neubiorev.2014.11.003 This meta-analysis is a good primer for understanding brain areas recruited across response inhibition tasks. CrossRefGoogle Scholar
  31. 31.
    Logan GD, Cowan WB. On the ability to inhibit thought and action: a theory of an act of control. Psychol Rev. 1984;91(3):295–327.  https://doi.org/10.1037//0033-295X.91.3.295.CrossRefGoogle Scholar
  32. 32.
    MacLeod CM. Half a century of research on the Stroop effect: an integrative review. Psychol Bull. 1991;109(2):163–203.  https://doi.org/10.1037//0033-2909.109.2.163.CrossRefGoogle Scholar
  33. 33.
    Schachar R, Logan GD, Robaey P, Chen S, Ickowicz A, Barr C. Restraint and cancellation: multiple inhibition deficits in attention deficit hyperactivity disorder. J Abnorm Child Psychol. 2007;35(2):229–38.  https://doi.org/10.1007/s10802-006-9075-2.CrossRefGoogle Scholar
  34. 34.
    Chikazoe J. Localizing performance of go/no-go tasks to prefrontal cortical subregions. Curr Opin Psychiatry. 2010;23(3):267–72.  https://doi.org/10.1097/YCO.0b013e3283387a9f.CrossRefGoogle Scholar
  35. 35.
    Verbruggen F, Aron AR, Stevens MA, Chambers CD. Theta burst stimulation dissociates attention and action updating in human inferior frontal cortex. Proc Natl Acad Sci U S A. 2010;107(31):13966–71.  https://doi.org/10.1073/pnas.1001957107.CrossRefGoogle Scholar
  36. 36.
    Sridharan D, Levitin DJ, Menon V. A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proc Natl Acad Sci U S A. 2008;105(34):12569–74.  https://doi.org/10.1073/pnas.0800005105.CrossRefGoogle Scholar
  37. 37.
    Sharp DJ, Bonnelle V, De Boissezon X, Beckmann CF, James SG, Patel MC, et al. Distinct frontal systems for response inhibition, attentional capture, and error processing. Proc Natl Acad Sci U S A. 2010;107(13):6106–11.  https://doi.org/10.1073/pnas.1000175107.
  38. 38.
    de Ruiter MB, Oosterlaan J, Veltman DJ, van den Brink W, Goudriaan AE. Similar hyporesponsiveness of the dorsomedial prefrontal cortex in problem gamblers and heavy smokers during an inhibitory control task. Drug Alcohol Depend. 2012;121(1–2):81–9.  https://doi.org/10.1016/j.drugalcdep.2011.08.010.CrossRefGoogle Scholar
  39. 39.
    Van Holst RJ, Van Holstein M, Van Den Brink W, Veltman DJ, Goudriaan AE. Response inhibition during cue reactivity in problem gamblers: an fMRI study. PLoS One. 2012;7(3):e30909.  https://doi.org/10.1371/journal.pone.0030909.CrossRefGoogle Scholar
  40. 40.
    • Ko CH, Hsieh TJ, Chen CY, Yen CF, Chen CS, Yen JY, et al. Altered brain activation during response inhibition and error processing in subjects with Internet gaming disorder: a functional magnetic imaging study. Eur Arch Psychiatry Clin Neurosci. 2014;264(8):661–72.  https://doi.org/10.1007/s00406-013-0483-3 This study examines neurobiological differences in control participants and individuals with IGD on the go/no-go task. Individuals with IGD demonstrate increased recruitment of diverse brain areas involving response inhibition in comparison with control subjects, when matched on task performance. CrossRefGoogle Scholar
  41. 41.
    • Chen CY, Huang MF, Yen JY, Chen CS, Liu GC, Yen CF, et al. Brain correlates of response inhibition in internet gaming disorder. Psychiatry Clin Neurosci. 2015;69(4):201–9.  https://doi.org/10.1111/pcn.12224 This paper examined neurobiological differences between control and participants with IGD on the go/no-go task. Individuals with IGD demonstrated lower activity in the supplementary motor area.
  42. 42.
    Liu GC, Yen JY, Chen CY, Yen CF, Chen CS, Lin WC, et al. Brain activation for response inhibition under gaming cue distraction in internet gaming disorder. Kaohsiung J Med Sci. 2014;30(1):43–51.  https://doi.org/10.1016/j.kjms.2013.08.005.
  43. 43.
    Luijten M, Meerkerk GJ, Franken IH, van de Wetering BJ, Schoenmakers TM. An fMRI study of cognitive control in problem gamers. Psychiatry Res Neuroimaging. 2015;231(3):262–8.  https://doi.org/10.1016/j.pscychresns.2015.01.004.CrossRefGoogle Scholar
  44. 44.
    Chikazoe J, Konishi S, Asari T, Jimura K, Miyashita Y. Activation of right inferior frontal gyrus during response inhibition across response modalities. J Cogn Neurosci. 2007;19(1):69–80.  https://doi.org/10.1162/jocn.2007.19.1.69.CrossRefGoogle Scholar
  45. 45.
    Ding, W. N., Sun, J. H., Sun, Y. W., Chen, X., Zhou, Y., Zhuang, Z. G., … & Du, Y. S. Trait impulsivity and impaired prefrontal impulse inhibition function in adolescents with internet gaming addiction revealed by a go/no-go fMRI study. Behav Brain Funct. 2014;10(1), 20.  https://doi.org/10.1186/1744-9081-10-20.
  46. 46.
    Chambers RA, Taylor JR, Potenza MN. Developmental neurocircuitry of motivation in adolescence: a critical period of addiction vulnerability. Am J Psychiatry. 2003;160(6):1041–52.  https://doi.org/10.1176/appi.ajp.160.6.1041.CrossRefGoogle Scholar
  47. 47.
    Bjork, J. M., Smith, A. R., Danube, C. L., & Hommer, D. W. (2007). Developmental differences in posterior mesofrontal cortex recruitment by risky rewards. J. Neurosci. 2007; 27(18), 4839–4849.  https://doi.org/10.1523/JNEUROSCI.5469-06.2007.
  48. 48.
    Leung HC, Skudlarski P, Gatenby JC, Peterson BS, Gore JC. An event-related functional MRI study of the Stroop color word interference task. Cereb Cortex. 2000;10(6):552–60.  https://doi.org/10.1093/cercor/10.6.552.CrossRefGoogle Scholar
  49. 49.
    Ridderinkhof KR, Van Den Wildenberg WP, Segalowitz SJ, Carter CS. Neurocognitive mechanisms of cognitive control: the role of prefrontal cortex in action selection, response inhibition, performance monitoring, and reward-based learning. Brain Cogn. 2004;56(2):129–40.  https://doi.org/10.1016/j.bandc.2004.09.016.CrossRefGoogle Scholar
  50. 50.
    Potenza, M. N., Leung, H. C., Blumberg, H. P., Peterson, B. S., Fulbright, R. K., Lacadie, C. M., … & Gore, J. C. An FMRI Stroop task study of ventromedial prefrontal cortical function in pathological gamblers. Am J Psychiatry 2003;160(11), 1990–1994.  https://doi.org/10.1176/appi.ajp.160.11.1990
  51. 51.
    Dong G, Devito EE, Du X, Cui Z. Impaired inhibitory control in ‘internet addiction disorder’: a functional magnetic resonance imaging study. Psychiatry Res Neuroimaging. 2012;203(2–3):153–8.  https://doi.org/10.1016/j.pscychresns.2012.02.001.CrossRefGoogle Scholar
  52. 52.
    • Zhang Y, Lin X, Zhou H, Xu J, Du X, Dong G. Brain activity toward gaming-related cues in Internet gaming disorder during an addiction stroop task. Front Psychol. 2016;7:714. This paper demonstrates that individuals with IGD show greater recruitment of specific brain regions when observing gaming-related stimuli during the Stroop task in comparison with control participants.  https://doi.org/10.3389/fpsyg.2016.00714.Google Scholar
  53. 53.
    MacKillop J, Amlung MT, Few LR, Ray LA, Sweet LH, Munafò MR. Delayed reward discounting and addictive behavior: a meta-analysis. Psychopharmacology. 2011;216(3):305–21.  https://doi.org/10.1007/s00213-011-2229-0.CrossRefGoogle Scholar
  54. 54.
    Saville BK, Gisbert A, Kopp J, Telesco C. Internet addiction and delay discounting in college students. Psychol Rec. 2010;60(2):273–86.  https://doi.org/10.1007/BF03395707.CrossRefGoogle Scholar
  55. 55.
    Dixon MR, Marley J, Jacobs EA. Delay discounting by pathological gamblers. J Appl Behav Anal. 2003;36(4):449–58.  https://doi.org/10.1901/jaba.2003.36-449.CrossRefGoogle Scholar
  56. 56.
    • Amlung M, Vedelago L, Acker J, Balodis I, MacKillop J. Steep delay discounting and addictive behavior: a meta-analysis of continuous associations. Addiction. 2017;112(1):51–62.  https://doi.org/10.1111/add.13535 This meta-analysis shows steep delay discounting across a wide range of addictive behaviour. CrossRefGoogle Scholar
  57. 57.
    Alessi SM, Petry NM. Pathological gambling severity is associated with impulsivity in a delay discounting procedure. Behav Process. 2003;64(3):345–54.  https://doi.org/10.1016/S0376-6357(03)00150-5.CrossRefGoogle Scholar
  58. 58.
    •• Miedl SF, Peters J, Büchel C. Altered neural reward representations in pathological gamblers revealed by delay and probability discounting. Arch Gen Psychiatry. 2012;69(2):177–86.  https://doi.org/10.1001/archgenpsychiatry.2011.1552 This paper examines the neurobiology of subjective reward value in both delay and probability discounting in pathological gambling. CrossRefGoogle Scholar
  59. 59.
    Miedl SF, Wiswede D, Marco-Pallarés J, Ye Z, Fehr T, Herrmann M, et al. The neural basis of impulsive discounting in pathological gamblers. Brain Imaging Behav. 2015;9(4):887–98.  https://doi.org/10.1007/s11682-015-9352-1.
  60. 60.
    Wang Y, Wu L, Zhou H, Lin X, Zhang Y, Du X, et al. Impaired executive control and reward circuit in Internet gaming addicts under a delay discounting task: independent component analysis. Eur Arch Psychiatry Clin Neurosci. 2017;267(3):245–55.  https://doi.org/10.1007/s00406-016-0721-6.
  61. 61.
    • Miedl SF, Büchel C, Peters J. Cue-induced craving increases impulsivity via changes in striatal value signals in problem gamblers. J Neurosci. 2014;34(13):4750–5.  https://doi.org/10.1523/JNEUROSCI.5020-13.2014 This study examines striatal and midbrain value signal responding in the presence of gambling cues in individuals with problem gambling . CrossRefGoogle Scholar
  62. 62.
    Christopoulos GI, Tobler PN, Bossaerts P, Dolan RJ, Schultz W. Neural correlates of value, risk, and risk aversion contributing to decision making under risk. J Neurosci. 2009;29(40):12574–83.  https://doi.org/10.1523/JNEUROSCI.2614-09.2009.CrossRefGoogle Scholar
  63. 63.
    Mohr PN, Biele G, Heekeren HR. Neural processing of risk. J Neurosci. 2010;30(19):6613–9.  https://doi.org/10.1523/JNEUROSCI.0003-10.2010.CrossRefGoogle Scholar
  64. 64.
    Bush G, Vogt BA, Holmes J, Dale AM, Greve D, Jenike MA, et al. Dorsal anterior cingulate cortex: a role in reward-based decision making. Proc Natl Acad Sci U S A. 2002;99(1):523–8.  https://doi.org/10.1073/pnas.012470999.
  65. 65.
    Botvinick M, Nystrom LE, Fissell K, Carter CS, Cohen JD. Conflict monitoring versus selection-for-action in anterior cingulate cortex. Nature. 1999;402(6758):179–81.  https://doi.org/10.1038/46035.CrossRefGoogle Scholar
  66. 66.
    O’Doherty, J. P. Reward representations and reward-related learning in the human brain: insights from neuroimaging. Curr. Opin. Neurobiol. 2004; 14(6), 769–776. https://doi.org/10.1016/j.conb.2004.10.016.
  67. 67.
    Swick D, Ashley V, Turken U. Left inferior frontal gyrus is critical for response inhibition. BMC Neurosci. 2008;9(1):102.  https://doi.org/10.1186/1471-2202-9-102.CrossRefGoogle Scholar
  68. 68.
    Hampshire A, Chamberlain SR, Monti MM, Duncan J, Owen AM. The role of the right inferior frontal gyrus: inhibition and attentional control. Neuroimage. 2010;50(3):1313–9.  https://doi.org/10.1016/j.neuroimage.2009.12.109.CrossRefGoogle Scholar
  69. 69.
    Balodis IM, Kober H, Worhunsky PD, Stevens MC, Pearlson GD, Potenza MN. Diminished frontostriatal activity during processing of monetary rewards and losses in pathological gambling. Biol Psychiatry. 2012;71(8):749–57.  https://doi.org/10.1016/j.biopsych.2012.01.006.CrossRefGoogle Scholar
  70. 70.
    Patel KT, Stevens MC, Meda SA, Muska C, Thomas AD, Potenza MN, et al. Robust changes in reward circuitry during reward loss in current and former cocaine users during performance of a monetary incentive delay task. Biol Psychiatry. 2013;74(7):529–37.  https://doi.org/10.1016/j.biopsych.2013.04.029.
  71. 71.
    Knutson B, Westdorp A, Kaiser E, Hommer D. FMRI visualization of brain activity during a monetary incentive delay task. Neuroimage. 2000;12(1):20–7.  https://doi.org/10.1006/nimg.2000.0593.CrossRefGoogle Scholar
  72. 72.
    Knutson B, Adams CM, Fong GW, Hommer D. Anticipation of increasing monetary reward selectively recruits nucleus accumbens. J Neurosci. 2001;21(16):RC159–9.  https://doi.org/10.1523/JNEUROSCI.21-16-j0002.2001.
  73. 73.
    Reuter J, Raedler T, Rose M, Hand I, Gläscher J, Büchel C. Pathological gambling is linked to reduced activation of the mesolimbic reward system. Nat Neurosci. 2005;8(2):147–8.  https://doi.org/10.1038/nn1378.CrossRefGoogle Scholar
  74. 74.
    Dong G, Li H, Wang L, Potenza MN. Cognitive control and reward/loss processing in Internet gaming disorder: results from a comparison with recreational Internet game-users. Eur Psychiatry. 2017;44:30–8.  https://doi.org/10.1016/j.eurpsy.2017.03.004.CrossRefGoogle Scholar
  75. 75.
    Choi J-S, Shin Y-C, Jung WH, Jang JH, Kang D-H, Choi C-H, et al. Altered brain activity during reward anticipation in pathological gambling and obsessive-compulsive disorder. PLoS One. 2012;7(9):e45938.  https://doi.org/10.1371/journal.pone.0045938.
  76. 76.
    Schultz W. Predictive reward signal of dopamine neurons. J Neurophysiol. 1998;80(1):1–27.  https://doi.org/10.1152/jn.1998.80.1.1.CrossRefGoogle Scholar
  77. 77.
    Romanczuk-Seiferth N, Koehler S, Dreesen C, Wüstenberg T, Heinz A. Pathological gambling and alcohol dependence: neural disturbances in reward and loss avoidance processing. Addict Biol 2015. 2015;20(3):557–69.  https://doi.org/10.1111/adb.12144.CrossRefGoogle Scholar
  78. 78.
    Beck A, Schlagenhauf F, Wüstenberg T, Hein J, Kienast T, Kahnt T, et al. Biol Psychiatry. 2009;66(8):734–42.  https://doi.org/10.1016/j.biopsych.2009.04.035.CrossRefGoogle Scholar
  79. 79.
    Andrews MM, Meda SA, Thomas AD, Potenza MN, Krystal JH, Worhunsky P, et al. Individuals family history positive for alcoholism show functional magnetic resonance imaging differences in reward sensitivity that are related to impulsivity factors. Biol Psychiatry. 2011;69(7):675–83.  https://doi.org/10.1016/j.biopsych.2010.09.049.CrossRefGoogle Scholar
  80. 80.
    •• Luijten M, Schellekens AF, Kühn S, Machielse MW, Sescousse G. Disruption of reward processing in addiction: an image-based meta-analysis of functional magnetic resonance imaging studies. JAMA Psychiatry. 2017;74(4):387–98.  https://doi.org/10.1001/jamapsychiatry.2016.3084 This is a large meta-analysis on reward processing across addictive behaviour, specifically examining the neural basis of anticipatory versus outcome processing across 600 individuals with substance and gambling addictions. CrossRefGoogle Scholar
  81. 81.
    Izuma K, Saito DN, Sadato N. Processing of social and monetary rewards in the human striatum. Neuron. 2008;58(2):284–94.  https://doi.org/10.1016/j.neuron.2008.03.020.CrossRefGoogle Scholar
  82. 82.
    de Ruiter MB, Veltman DJ, Goudriaan AE, Oosterlaan J, Sjoerds Z, Van Den Brink W. Response perseveration and ventral prefrontal sensitivity to reward and punishment in male problem gamblers and smokers. Neuropsychopharmacology. 2009;34(4):1027–38.  https://doi.org/10.1038/npp.2008.175.CrossRefGoogle Scholar
  83. 83.
    Badre D, Wagner AD. Left ventrolateral prefrontal cortex and the cognitive control of memory. Neuropsychologia. 2007;45(13):2883–901.  https://doi.org/10.1016/j.neuropsychologia.2007.06.015.CrossRefGoogle Scholar
  84. 84.
    Deng W, Rolls ET, Ji X, Robbins TW, Banaschewski T, Bokde AL, et al. Separate neural systems for behavioral change and for emotional responses to failure during behavioral inhibition. Hum Brain Mapp. 2017;38(7):3527–37.  https://doi.org/10.1002/hbm.23607.Google Scholar
  85. 85.
    Pontes HM, Griffiths MD. Measuring DSM-5 Internet gaming disorder: development and validation of a short psychometric scale. Comput Hum Behav. 2015;45:137–43.  https://doi.org/10.1016/j.chb.2014.12.006.CrossRefGoogle Scholar
  86. 86.
    Lemmens JS, Valkenburg PM, Peter J. Development and validation of a game addiction scale for adolescents. Media Psychol. 2009;12(1):77–95.  https://doi.org/10.1080/15213260802669458.CrossRefGoogle Scholar
  87. 87.
    Hodgins DC, Stea JN, Grant JE. Gambling disorders. Lancet. 2011;378(9806):1874–84.  https://doi.org/10.1016/S0140-6736(10)62185-X.CrossRefGoogle Scholar
  88. 88.
    Grant JE, Chamberlain SR. Impulsive action and impulsive choice across substance and behavioral addictions: cause or consequence? Addict Behav. 2014;39(11):1632–9.  https://doi.org/10.1016/j.addbeh.2014.04.022.CrossRefGoogle Scholar
  89. 89.
    Verdejo-García A, Lawrence AJ, Clark L. Impulsivity as a vulnerability marker for substance-use disorders: review of findings from high-risk research, problem gamblers and genetic association studies. Neurosci Biobehav Rev. 2008;32(4):777–810.  https://doi.org/10.1016/j.neubiorev.2007.11.003.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Psychiatry & Behavioural NeurosciencesMcMaster UniversityHamiltonCanada
  2. 2.Peter Boris Centre for Addictions ResearchSt. Joseph’s Healthcare HamiltonHamiltonCanada
  3. 3.Michael G. DeGroote Centre for Medicinal Cannabis ResearchHamiltonCanada

Personalised recommendations