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Neuroimaging of the dopamine/reward system in adolescent drug use

Published online by Cambridge University Press:  22 June 2015

Monique Ernst  and
Monica Luciana
Monique Ernst*
Affiliation:
Neurodevelopment of Reward Systems Program, National Institute of Mental Health, Bethesda, Maryland, USA
Monica Luciana
Affiliation:
Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
*
*Address for correspondence: Monique Ernst, MD, PhD, Head of Neurodevelopment of Reward Systems, Section on Neurobiology of Fear and Anxiety (NFA), Emotional Development and Affective Neuroscience Branch (EDAN), National Institute of Mental Health/NIH, 15K North Drive, Bethesda, MD 20892, USA. (Email: [email protected])
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Abstract

Adolescence is characterized by heightened risk-taking, including substance misuse. These behavioral patterns are influenced by ontogenic changes in neurotransmitter systems, particularly the dopamine system, which is fundamentally involved in the neural coding of reward and motivated approach behavior. During adolescence, this system evidences a peak in activity. At the same time, the dopamine (DA) system is neuroplastically altered by substance abuse, impacting subsequent function. Here, we describe properties of the dopamine system that change with typical adolescent development and that are altered with substance abuse. Much of this work has been gleaned from animal models due to limitations in measuring dopamine in pediatric samples. Structural and functional neuroimaging techniques have been used to examine structures that are heavily DA-innervated; they measure morphological and functional changes with age and with drug exposure. Presenting marijuana abuse as an exemplar, we consider recent findings that support an adolescent peak in DA-driven reward-seeking behavior and related deviations in motivational systems that are associated with marijuana abuse/dependence. Clinicians are advised that (1) chronic adolescent marijuana use may lead to deficiencies in incentive motivation, (2) that this state is due to marijuana’s interactions with the developing DA system, and (3) that treatment strategies should be directed to remediating resultant deficiencies in goal-directed activity.

Keywords

adolescencesubstance abusemarijuanastriatumdopamineneuroimaging
Type
Review Articles
Information
CNS Spectrums , Volume 20 , Special Issue 4: Pediatric Neuroimaging , August 2015 , pp. 427 - 441
Copyright
© Cambridge University Press 2015 

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References

1. Johnston, LD, O’Malley, PM, Bachman, JG, Schulenberg, JE. Monitoring the Future national results on adolescent drug use: Overview of key findings, 2010. Ann Arbor, MI: Institute for Social Research, The University of Michigan, 2011.Google Scholar
2. Sustance Abuse and Mental Health Services Adminstration. The NSDUH Report: Trends in Adolescent Substance Use and Perception of Risk from Substance Use. Sustance Abuse and Mental Health Services Adminstration: Rockville, MD; 2013.Google Scholar
3. Eaton, DK, Kann, L, Kinchen, S, et al. Youth Behavior Surveillance—United States, 2011. Atlanta, GA: CDC; 2012.Google Scholar
4. U.S. Department of Health and Human Services, Sustance Abuse and Mental Health Services Adminstration. Results from the 2010 National Survey on Drug Use and Health: Summary of National Findings. Rockville, MD: Sustance Abuse and Mental Health Services Adminstration; 2011.Google Scholar
5. Merikangas, KR, Nakamura, EF, Kessler, RC. Epidemiology of mental disorders in children and adolescents. Dialogues Clin Neurosci. 2009; 11(1): 7–20.Google Scholar
6. Armstrong, TD, Costello, EJ. Community studies on adolescent substance use, abuse, or dependence and psychiatric comorbidity. J COnsult Clin Psychol. 2002; 70(6): 1224–1239.Google Scholar
7. Arnett, JJ. Adolescent storm and stress, reconsidered. Am Psychol. 1999; 54(5): 317–326.Google Scholar
8. Dahl, RE. Adolescent brain development: a period of vulnerabilities and opportunities. Keynote address. Ann N Y Acad Sci. 2004; 1021: 1–22.CrossRefGoogle ScholarPubMed
9. Ernst, M, Pine, DS, Hardin, M. Triadic model of the neurobiology of motivated behavior in adolescence. Psychol Med. 2006; 36(3): 299–312.Google Scholar
10. Nelson, EE, Leibenluft, E, McClure, EB, Pine, DS. The social re-orientation of adolescence: a neuroscience perspective on the process and its relation to psychopathology. Psychol Med. 2005; 35(2): 163–174.Google Scholar
11. Steinberg, L. Risk taking in adolescence: what changes, and why? Ann N Y Acad SciAnn N Y Acad Sci. 2004; 1021: 51–58.Google Scholar
12. Ernst, M, Hale, E, O’Connell, K. Response to commentaries regarding the Triadic Systems Model perspective. Brain Cogn. 2014; 89: 122–126.Google Scholar
13. Arnett, JJ. G. Stanley Hall’s Adolescence: brilliance and nonsense. Hist Psychol. 2006; 9(3): 186–197.Google Scholar
14. Hall, G. Adolescence: Its Psychology and Its Relations to Physiology, Anthropology, Sociology, Sex, Crime, Religion and Education. New York: Appleton; 1904.Google Scholar
15. Spear, LP. The adolescent brain and age-related behavioral manifestations. Neurosci Biobehav Rev. 2000; 24(4): 417–463.Google Scholar
16. Ernst, M, Romeo, RD, Andersen, SL. Neurobiology of the development of motivated behaviors in adolescence: a window into a neural systems model. Pharmacol Biochem Behav. 2009; 93(3): 199–211.Google Scholar
17. Wahlstrom, D, Collins, P, White, T, Luciana, M. Developmental changes in dopamine neurotransmission in adolescence: behavioral implications and issues in assessment. Brain Cogn. 2010; 72(1): 146–159.CrossRefGoogle ScholarPubMed
18. Robbins, TW, Everitt, BJ. Neurobehavioural mechanisms of reward and motivation. Curr Opin Neurobiol. 1996; 6(2): 228–236.Google Scholar
19. Koob, GF, Volkow, ND. Neurocircuitry of addiction. Neuropsychopharmacology. 2010; 35(1): 217–238.Google Scholar
20. Goldstein, RZ, Volkow, ND. Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nat Rev Neurosci. 2011; 12(11): 652–669.CrossRefGoogle ScholarPubMed
21. Garavan, H, Weierstall, K. The neurobiology of reward and cognitive control systems and their role in incentivizing health behavior. Prev Med. 2012; 55(Suppl): S17–S23.CrossRefGoogle ScholarPubMed
22. Wise, RA, Rompre, PP. Brain dopamine and reward. Annu Rev Psychol. 1989; 40: 191–225.Google Scholar
23. Wise, RA. Neurobiology of addiction. Curr Opin Neurobiol. 1996; 6(2): 243–251.Google Scholar
24. Volkow, ND, Fowler, JS, Wang, GJ. The addicted human brain: insights from imaging studies. J Clin Invest. 2003; 111(10): 1444–1451.Google Scholar
25. Luciana, M, Wahlstrom, D, Porter, JN, Collins, PF. Dopaminergic modulation of incentive motivation in adolescence: age-related changes in signaling, individual differences, and implications for the development of self-regulation. Dev Psychol. 2012; 48(3): 844–861.Google Scholar
26. Carlsson, A, Lindqvist, M, Magnusson, T. 3,4-Dihydroxyphenylalanine and 5-hydroxytryptophan as reserpine antagonists. Nature. 1957; 180(4596): 1200.Google Scholar
27. Beaulieu, JM, Gainetdinov, RR. The physiology, signaling, and pharmacology of dopamine receptors. Pharmacol Rev. 2011; 63(1): 182–217.Google Scholar
28. Bjorklund, A, Dunnett, SB. Dopamine neuron systems in the brain: an update. Trends Neurosci. 2007; 30(5): 194–202.Google Scholar
29. Moore, H, West, AR, Grace, AA. The regulation of forebrain dopamine transmission: relevance to the pathophysiology and psychopathology of schizophrenia. Biol Psychiatry. 1999; 46(1): 40–55.Google Scholar
30. Nemoda, Z, Szekely, A, Sasvari-Szekely, M. Psychopathological aspects of dopaminergic gene polymorphisms in adolescence and young adulthood. Neurosci Biobehav Rev. 2011; 35(8): 1665–1686.Google Scholar
31. Joyce, JN. Multiple dopamine receptors and behavior. Neurosci Biobehav Rev. 1983; 7(2): 227–256.Google Scholar
32. Kohno, M, Ghahremani, DG, Morales, AM, et al. Risk-taking behavior: dopamine D2/D3 receptors, feedback, and frontolimbic activity. Cereb Cortex. 2015; 25(1): 236–245.Google Scholar
33. Missale, C, Nash, SR, Robinson, SW, Jaber, M, Caron, MG. Dopamine receptors: from structure to function. Physiol Rev. 1998; 78(1): 189–225.Google Scholar
34. Floresco, SB, Magyar, O. Mesocortical dopamine modulation of executive functions: beyond working memory. Psychopharmacology (Berl). 2006; 188(4): 567–585.Google Scholar
35. Depue, RA, Collins, PF. Neurobiology of the structure of personality: dopamine, facilitation of incentive motivation, and extraversion. Behav Brain Sci. 1999; 22(3): 491–517; discussion 518–569.CrossRefGoogle ScholarPubMed
36. Swanson, LW. The projections of the ventral tegmental area and adjacent regions: a combined fluorescent retrograde tracer and immunofluorescence study in the rat. Brain Res Bull. 1982; 9(1–6): 321–353.Google Scholar
37. Kaczmarek, LK, Levitan, I. Neuromodulation: The Biochemical Control of Neuronal Excitability. Oxford, England: Oxford University Press; 1987.Google Scholar
38. Trudeau, LE. Glutamate co-transmission as an emerging concept in monoamine neuron function. J Psychiatry Neurosci. 2004; 29(4): 296–310.Google Scholar
39. Luciana, M, Collins, PF. Incentive motivation, cognitive control, and the adolescent brain: is it time for a paradigm shift? Child Dev Perspect. 2012; 6(4): 392–399.Google Scholar
40. Garris, PA, Rebec, GV. Modeling fast dopamine neurotransmission in the nucleus accumbens during behavior. Behav Brain Res. 2002; 137(1–2): 47–63.Google Scholar
41. Rice, ME, Cragg, SJ. Dopamine spillover after quantal release: rethinking dopamine transmission in the nigrostriatal pathway. Brain Res Rev. 2008; 58(2): 303–313.Google Scholar
42. Floresco, SB, West, AR, Ash, B, Moore, H, Grace, AA. Afferent modulation of dopamine neuron firing differentially regulates tonic and phasic dopamine transmission. Nature Neurosci. 2003; 6(9): 968–973.Google Scholar
43. Goto, Y, Otani, S, Grace, AA. The yin and yang of dopamine release: a new perspective. Neuropharmacology. 2007; 53(5): 583–587.Google Scholar
44. Grace, AA, Bunney, BS. The control of firing pattern in nigral dopamine neurons: burst firing. J Neurosci. 1984; 4(11): 2877–2890.Google Scholar
45. Grace, AA, Bunney, BS. The control of firing pattern in nigral dopamine neurons: single spike firing. J Neurosci. 1984; 4(11): 2866–2876.Google Scholar
46. Wanat, MJ, Willuhn, I, Clark, JJ, Phillips, PE. Phasic dopamine release in appetitive behaviors and drug addiction. Curr Drug Abuse Rev. 2009; 2(2): 195–213.Google Scholar
47. Willuhn, I, Wanat, MJ, Clark, JJ, Phillips, PE. Dopamine signaling in the nucleus accumbens of animals self-administering drugs of abuse. Curr Top Behav Neurosci. 2010; 3: 29–71.Google Scholar
48. Schultz, W. Multiple reward signals in the brain. Nat Rev Neurosci. 2000; 1(3): 199–207.CrossRefGoogle ScholarPubMed
49. Niv, Y, Joel, D, Dayan, P. A normative perspective on motivation. Trends Cogn Sci. 2006; 10(8): 375–381.Google Scholar
50. Niv, Y, Daw, ND, Joel, D, Dayan, P. Tonic dopamine: opportunity costs and the control of response vigor. Psychopharmacology (Berl). 2007; 191(3): 507–520.Google Scholar
51. Ostlund, SB, Wassum, KM, Murphy, NP, Balleine, BW, Maidment, NT. Extracellular dopamine levels in striatal subregions track shifts in motivation and response cost during instrumental conditioning. J Neurosci. 2011; 31(1): 200–207.Google Scholar
52. Wahlstrom, D, White, T, Luciana, M. Neurobehavioral evidence for changes in dopamine system activity during adolescence. Neurosci Biobehav Rev. 2010; 34(5): 631–648.Google Scholar
53. Andersen, SL, Dumont, NL, Teicher, MH. Developmental differences in dopamine synthesis inhibition by (+/-)-7-OH-DPAT. Naunyn Schmiedebergs Arch Pharmacol. 1997; 356(2): 173–181.Google Scholar
54. Gelbard, HA, Teicher, MH, Faedda, G, Baldessarini, RJ. Postnatal development of dopamine D1 and D2 receptor sites in rat striatum. Brain Res Dev Brain Res. 1989; 49(1): 123–130.Google Scholar
55. Tarazi, FI, Tomasini, EC, Baldessarini, RJ. Postnatal development of dopamine D1-like receptors in rat cortical and striatolimbic brain regions: an autoradiographic study. Dev Neurosci. 1999; 21(1): 43–49.Google Scholar
56. Teicher, MH, Andersen, SL, Hostetter, JC Jr. Evidence for dopamine receptor pruning between adolescence and adulthood in striatum but not nucleus accumbens. Brain Res Dev Brain Res. 1995; 89(2): 167–172.Google Scholar
57. Giorgi, O, De Montis, G, Porceddu, ML, et al. Developmental and age-related changes in D1-dopamine receptors and dopamine content in the rat striatum. Brain Res. 1987; 432(2): 283–290.Google Scholar
58. Leslie, CA, Robertson, MW, Cutler, AJ, Bennett, JP Jr. Postnatal development of D1 dopamine receptors in the medial prefrontal cortex, striatum and nucleus accumbens of normal and neonatal 6-hydroxydopamine treated rats: a quantitative autoradiographic analysis. Brain Res Dev Brain Res. 1991; 62(1): 109–114.Google Scholar
59. Tarazi, FI, Tomasini, EC, Baldessarini, RJ. Postnatal development of dopamine D4-like receptors in rat forebrain regions: comparison with D2-like receptors. Brain Res Dev Brain Res. 1998; 110(2): 227–233.Google Scholar
60. Rao, PA, Molinoff, PB, Joyce, JN. Ontogeny of dopamine D1 and D2 receptor subtypes in rat basal ganglia: a quantitative autoradiographic study. Brain Res Dev Brain Res. 1991; 60(2): 161–177.CrossRefGoogle ScholarPubMed
61. Goto, Y, Grace, AA. Dopaminergic modulation of limbic and cortical drive of nucleus accumbens in goal-directed behavior. Nat Neurosci. 2005; 8(6): 805–812.Google Scholar
62. Jia, JM, Zhao, J, Hu, Z, Lindberg, D, Li, Z. Age-dependent regulation of synaptic connections by dopamine D2 receptors. Nat Neurosci. 2013; 16(11): 1627–1636.Google Scholar
63. Crews, F, He, J, Hodge, C. Adolescent cortical development: a critical period of vulnerability for addiction. Pharmacol Biochem Behav. 2007; 86(2): 189–199.Google Scholar
64. Selemon, LD. A role for synaptic plasticity in the adolescent development of executive function. Transl Psychiatry. 2013; 3: e238.Google Scholar
65. Selemon, LD. Frontal lobe synaptic plasticity in development and disease: modulation by the dopamine d1 receptor. Curr Pharm Des. 2014; 20(32): 5194–5201.Google Scholar
66. Sun, X, Zhao, Y, Wolf, ME. Dopamine receptor stimulation modulates AMPA receptor synaptic insertion in prefrontal cortex neurons. J Neurosci. 2005; 25(32): 7342–7351.Google Scholar
67. Auclair, N, Otani, S, Soubrie, P, Crepel, F. Cannabinoids modulate synaptic strength and plasticity at glutamatergic synapses of rat prefrontal cortex pyramidal neurons. J Neurophysiol. 2000; 83(6): 3287–3293.Google Scholar
68. Pascual, M, Boix, J, Felipo, V, Guerri, C. Repeated alcohol administration during adolescence causes changes in the mesolimbic dopaminergic and glutamatergic systems and promotes alcohol intake in the adult rat. J Neurochem. 2009; 108(4): 920–931.Google Scholar
69. McCutcheon, JE, Conrad, KL, Carr, SB, Ford, KA, McGehee, DS, Marinelli, M. Dopamine neurons in the ventral tegmental area fire faster in adolescent rats than in adults. J Neurophysiol. 2012; 108(6): 1620–1630.Google Scholar
70. Harden, KP, Tucker-Drob, EM. Individual differences in the development of sensation seeking and impulsivity during adolescence: further evidence for a dual systems model. Dev Psychol. 2011; 47(3): 739–746.Google Scholar
71. Steinberg, L, Albert, D, Cauffman, E, Banich, M, Graham, S, Woolard, J. Age differences in sensation seeking and impulsivity as indexed by behavior and self-report: evidence for a dual systems model. Dev Psychol. 2008; 44(6): 1764–1778.Google Scholar
72. Urosevic, S, Collins, P, Muetzel, R, Lim, K, Luciana, M. Longitudinal changes in behavioral approach system sensitivity and brain structures involved in reward processing during adolescence. Dev Psychol. 2012; 48(5): 1488–1500.Google Scholar
73. Bjork, JM, Pardini, DA. Who are those “risk-taking adolescents”? Individual differences in developmental neuroimaging research. Dev Cogn Neurosci. 2015; 11: 56–64.Google Scholar
74. Richards, JM, Plate, RC, Ernst, M. A systematic review of fMRI reward paradigms used in studies of adolescents vs. adults: the impact of task design and implications for understanding neurodevelopment. Neurosci Biobehav Rev. 2013; 37(5): 976–991.Google Scholar
75. Joel, D, Weiner, I. The connections of the dopaminergic system with the striatum in rats and primates: an analysis with respect to the functional and compartmental organization of the striatum. Neuroscience. 2000; 96(3): 451–474.Google Scholar
76. Cohen, JR, Asarnow, RF, Sabb, FW, et al. A unique adolescent response to reward prediction errors. Nat Neurosci. 2010; 13(6): 669–671.Google Scholar
77. Di Chiara, G. Drug addiction as dopamine-dependent associative learning disorder. Eur J Pharmacol. 1999; 375(1–3): 13–30.Google Scholar
78. Di Chiara, G, Imperato, A. Drugs abused by humans preferentially increase synaptic dopamine concentrations in the mesolimbic system of freely moving rats. Proc Natl Acad Sci U S A. 1988; 85(14): 5274–5278.Google Scholar
79. Fiorino, DF, Coury, A, Phillips, AG. Dynamic changes in nucleus accumbens dopamine efflux during the Coolidge effect in male rats. J Neurosci. 1997; 17(12): 4849–4855.Google Scholar
80. Grace, AA. The tonic/phasic model of dopamine system regulation and its implications for understanding alcohol and psychostimulant craving. Addiction. 2000; 95(Suppl 2): S119–S128.Google Scholar
81. Mastwal, S, Ye, Y, Ren, M, et al. Phasic dopamine neuron activity elicits unique mesofrontal plasticity in adolescence. J Neurosci. 2014; 34(29): 9484–9496.Google Scholar
82. Howe, MW, Tierney, PL, Sandberg, SG, Phillips, PE, Graybiel, AM. Prolonged dopamine signalling in striatum signals proximity and value of distant rewards. Nature. 2013; 500(7464): 575–579.Google Scholar
83. Kolb, B. Brain plasticity and behavioral change. In: Craik F, Robert M, Sabourin M, eds. Advances in Psychological Science, Volume 2: Biological and Cognitive Aspects. East Sussex, UK: Psychology Press; 1998.Google Scholar
84. Robinson, TE, Kolb, B. Persistent structural modifications in nucleus accumbens and prefrontal cortex neurons produced by previous experience with amphetamine. J Neurosci. 1997; 17(21): 8491–8497.Google Scholar
85. Volkow, ND, Fowler, JS, Gatley, SJ, et al. PET evaluation of the dopamine system of the human brain. J Nucl Med. 1996; 37(7): 1242–1256.Google Scholar
86. Mizrahi, R. Advances in PET analyses of stress and dopamine. Neuropsychopharmacology. 2010; 35(1): 348–349.Google Scholar
87. Jucaite, A, Fernell, E, Halldin, C, Forssberg, H, Farde, L. Reduced midbrain dopamine transporter binding in male adolescents with attention-deficit/hyperactivity disorder: association between striatal dopamine markers and motor hyperactivity. Biol Psychiatry. 2005; 57(3): 229–238.Google Scholar
88. D’Ardenne, K, McClure, SM, Nystrom, LE, Cohen, JD. BOLD responses reflecting dopaminergic signals in the human ventral tegmental area. Science. 2008; 319(5867): 1264–1267.Google Scholar
89. Eapen, M, Zald, DH, Gatenby, JC, Ding, Z, Gore, JC. Using high-resolution MR imaging at 7T to evaluate the anatomy of the midbrain dopaminergic system. AJNR Am J Neuroradiol. 2011; 32(4): 688–694.CrossRefGoogle ScholarPubMed
90. Sustance Abuse and Mental Health Services Adminstration. Results from the 2005 National Survey on Drug Use and Health: National Findings. Rockville, MD: Office of Applied Studies; 2006. DHHS Publication No. SMA 06-4194.Google Scholar
91. Johnston, LD, O’Malley, PM, Miech, RA, Bachman, JG, Schulenberg, JE. Overview key findings on adolescent drug use. Sponsored by the National Institute on Drug Abuse at the National Institutes of Health, Monitoring the Future. Survey results on drug use 1975-2014, http://www.monitoringthefuture.org/pubs/monographs/mtf-overview2014.pdf.Google Scholar
92. Volkow, ND, Baler, RD, Compton, WM, Weiss, SR. Adverse health effects of marijuana use. New Engl J Med. 2014; 370(23): 2219–2227.Google Scholar
93. Gorelick, DA, Levin, KH, Copersino, ML, et al. Diagnostic criteria for cannabis withdrawal syndrome. Drug Alcohol Depend. 2012; 123(1–3): 141–147.Google Scholar
94. Oleson, EB, Cheer, JF. A brain on cannabinoids: the role of dopamine release in reward seeking. Cold Spring Harb Perspect Med. 2012; 2: 1–13.Google Scholar
95. Schweinsburg, AD, Brown, SA, Tapert, SF. The influence of marijuana use on neurocognitive functioning in adolescents. Curr Drug Abuse Rev. 2008; 1(1): 99–111.Google Scholar
96. Puig, MV, Rose, J, Schmidt, R, Freund, N. Dopamine modulation of learning and memory in the prefrontal cortex: insights from studies in primates, rodents, and birds. Front Neural Circuits. 2014; 8: 93.Google Scholar
97. Burns, HD, Van Laere, K, Sanabria-Bohorquez, S, et al. [18F]MK-9470, a positron emission tomography (PET) tracer for in vivo human PET brain imaging of the cannabinoid-1 receptor. Proc Natl Acad Sci U S A. 2007; 104(23): 9800–9805.Google Scholar
98. Gilman, JM, Kuster, JK, Lee, S, et al. Cannabis use is quantitatively associated with nucleus accumbens and amygdala abnormalities in young adult recreational users. J Neurosci. 2014; 34(16): 5529–5538.Google Scholar
99. Dennison, M, Whittle, S, Yucel, M, et al. Mapping subcortical brain maturation during adolescence: evidence of hemisphere- and sex-specific longitudinal changes. Dev Sci. 2013; 16(5): 772–791.Google Scholar
100. Ostby, Y, Tamnes, CK, Fjell, AM, Westlye, LT, Due-Tonnessen, P, Walhovd, KB. Heterogeneity in subcortical brain development: a structural magnetic resonance imaging study of brain maturation from 8 to 30 years. J Neurosci. 2009; 29(38): 11772–11782.Google Scholar
101. Schneider, S, Peters, J, Bromberg, U, et al. Risk taking and the adolescent reward system: a potential common link to substance abuse. Am J Psychiatry. 2012; 169(1): 39–46.Google Scholar
102. Urošević, S, Collins, P, Muetzel, R, Lim, KO, Luciana, M. Pubertal status associations with reward and threat sensitivities and subcortical brain volumes during adolescence. Brain Cogn. 2014; 89: 15–26.Google Scholar
103. Arnone, D, Barrick, TR, Chengappa, S, Mackay, CE, Clark, CA, Abou-Saleh, MT. Corpus callosum damage in heavy marijuana use: preliminary evidence from diffusion tensor tractography and tract-based spatial statistics. Neuroimage. 2008; 41(3): 1067–1074.Google Scholar
104. Ashtari, M, Cervellione, K, Cottone, J, Ardekani, BA, Sevy, S, Kumra, S. Diffusion abnormalities in adolescents and young adults with a history of heavy cannabis use. J Psychiatr Res. 2009; 43(3): 189–204.Google Scholar
105. Gruber, SA, Dahlgren, MK, Sagar, KA, Gonenc, A, Lukas, SE. Worth the wait: effects of age of onset of marijuana use on white matter and impulsivity. Psychopharmacology (Berl). 2014; 231(8): 1455–1465.Google Scholar
106. Gruber, SA, Silveri, MM, Dahlgren, MK, Yurgelun-Todd, D. Why so impulsive? White matter alterations are associated with impulsivity in chronic marijuana smokers. Exp Clin Psychopharmacol. 2011; 19(3): 231–242.Google Scholar
107. Heimer, L, Alheid, GF. Piecing together the puzzle of basal forebrain anatomy. Adv Exp Med Biol. 1991; 295: 1–42.Google Scholar
108. Kolb, B, Gorny, G, Limebeer, CL, Parker, LA. Chronic treatment with Delta-9-tetrahydrocannabinol alters the structure of neurons in the nucleus accumbens shell and medial prefrontal cortex of rats. Synapse. 2006; 60(6): 429–436.Google Scholar
109. Cousijn, J, Wiers, RW, Ridderinkhof, KR, van den Brink, W, Veltman, DJ, Goudriaan, AE. Grey matter alterations associated with cannabis use: results of a VBM study in heavy cannabis users and healthy controls. Neuroimage. 2012; 59(4): 3845–3851.Google Scholar
110. Lorenzetti, V, Lubman, DI, Whittle, S, Solowij, N, Yucel, M. Structural MRI findings in long-term cannabis users: what do we know? Subst Use Misuse. 2010; 45(11): 1787–1808.Google Scholar
111. Jager, G, Ramsey, NF. Long-term consequences of adolescent cannabis exposure on the development of cognition, brain structure and function: an overview of animal and human research. Curr Drug Abuse Rev. 2008; 1(2): 114–123.Google Scholar
112. Batalla, A, Bhattacharyya, S, Yucel, M, et al. Structural and functional imaging studies in chronic cannabis users: a systematic review of adolescent and adult findings. PLoS One. 2013; 8(2): e55821.Google Scholar
113. Volkow, ND, Wang, GJ, Telang, F, et al. Decreased dopamine brain reactivity in marijuana abusers is associated with negative emotionality and addiction severity. Proc Natl Acad Sci U S A. 2014; 111(30): E3149–E3156.Google Scholar
114. Albrecht, DS, Skosnik, PD, Vollmer, JM, et al. Striatal D(2)/D(3) receptor availability is inversely correlated with cannabis consumption in chronic marijuana users. Drug Alcohol Depend. 2013; 128(1–2): 52–57.Google Scholar
115. Sevy, S, Smith, GS, Ma, Y, et al. Cerebral glucose metabolism and D2/D3 receptor availability in young adults with cannabis dependence measured with positron emission tomography. Psychopharmacology (Berl). 2008; 197(4): 549–556.Google Scholar
116. Stokes, PR, Egerton, A, Watson, B, et al. History of cannabis use is not associated with alterations in striatal dopamine D2/D3 receptor availability. J Psychopharmacol. 2012; 26(1): 144–149.Google Scholar
117. Urban, NB, Slifstein, M, Thompson, JL, et al. Dopamine release in chronic cannabis users: a [11c]raclopride positron emission tomography study. Biol Psychiatry. 2012; 71(8): 677–683.Google Scholar
118. Bloomfield, MA, Morgan, CJ, Kapur, S, Curran, HV, Howes, OD. The link between dopamine function and apathy in cannabis users: an [18F]-DOPA PET imaging study. Psychopharmacology (Berl). 2014; 231(11): 2251–2259.Google Scholar
119. Murray, JE, Dilleen, R, Pelloux, Y, et al. Increased impulsivity retards the transition to dorsolateral striatal dopamine control of cocaine seeking. Biol Psychiatry. 2014; 76(1): 15–22.CrossRefGoogle ScholarPubMed
120. Nestor, L, Hester, R, Garavan, H. Increased ventral striatal BOLD activity during non-drug reward anticipation in cannabis users. Neuroimage. 2010; 49(1): 1133–1143.Google Scholar
121. van Hell, HH, Vink, M, Ossewaarde, L, Jager, G, Kahn, RS, Ramsey, NF. Chronic effects of cannabis use on the human reward system: an fMRI study. Eur Neuropsychopharmacol. 2010; 20(3): 153–163.Google Scholar
122. Sneider, JT, Mashhoon, Y, Silveri, MM. A review of magnetic resonance spectroscopy studies in marijuana using adolescents and adults. J Addict Res Ther. 2013; Suppl 4.Google Scholar
123. Silveri, MM, Jensen, JE, Rosso, IM, Sneider, JT, Yurgelun-Todd, DA. Preliminary evidence for white matter metabolite differences in marijuana-dependent young men using 2D J-resolved magnetic resonance spectroscopic imaging at 4 Tesla. Psychiatry Res. 2011; 191(3): 201–211.Google Scholar
124. Hermann, D, Sartorius, A, Welzel, H, et al. Dorsolateral prefrontal cortex N-acetylaspartate/total creatine (NAA/tCr) loss in male recreational cannabis users. Biol Psychiatry. 2007; 61(11): 1281–1289.Google Scholar
125. Chang, L, Cloak, C, Yakupov, R, Ernst, T. Combined and independent effects of chronic marijuana use and HIV on brain metabolites. J Neuroimmune Pharmacol. 2006; 1(1): 65–76.Google Scholar
126. Muetzel, RL, Marjanska, M, Collins, PF, et al. In vivo H magnetic resonance spectroscopy in young-adult daily marijuana users. Neuroimage Clin. 2013; 2: 581–589.Google Scholar
127. Prescot, AP, Locatelli, AE, Renshaw, PF, Yurgelun-Todd, DA. Neurochemical alterations in adolescent chronic marijuana smokers: a proton MRS study. Neuroimage. 2011; 57(1): 69–75.Google Scholar
128. Kalivas, PW, Volkow, ND. The neural basis of addiction: a pathology of motivation and choice. American J Psychiatry. 2005; 162(8): 1403–1413.Google Scholar
129. Hakamata, Y, Lissek, S, Bar-Haim, Y, et al. Attention bias modification treatment: a meta-analysis toward the establishment of novel treatment for anxiety. Biol Psychiatry. 2010; 68(11): 982–990.Google Scholar
130. Field, M, Marhe, R, Franken, IH. The clinical relevance of attentional bias in substance use disorders. CNS Spectr. 2014; 19(3): 225–230.Google Scholar
131. Sample, S, Kadden, R. Motivational Enhancement Therapy and Cognitive Behavioral Therapy for Adolescent Cannabis Users: 5 Sessions. Rockville, MD: Center for Substance Abuse Treatment; 2001.Google Scholar
132. Dennis, M, Titus, JC, Diamond, G, et al. The Cannabis Youth Treatment (CYT) experiment: rationale, study design and analysis plans. Addiction. 2002; 97(Suppl 1): 16–34.Google Scholar
133. Dennis, M, Godley, SH, Diamond, G, et al. The Cannabis Youth Treatment (CYT) Study: main findings from two randomized trials. J Subst Abuse Treat. 2004; 27(3): 197–213.Google Scholar