Skip to main content

Advertisement

SpringerLink
Log in

Current Understanding of the Neurobiology of Opioid Use Disorder: an Overview

  • Addictions (M Potenza and M Brand, Section Editors)
  • Published:
Current Behavioral Neuroscience Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

This review provides an overview of the neurobiological mechanisms underlying opioid use disorder (OUD) drawing from genetic, functional, and structural magnetic resonance imaging (MRI) research.

Recent Findings

Preliminary evidence suggests an association between OUD and specific variants of the DRD2, δ-opioid receptor 1 (OPRD1), and μ-opioid receptor 1 (OPRM1) genes. Additionally, MRI research indicates functional and structural alterations in striatal and corticolimbic brain regions and pathways underlying reward, emotion/stress, and cognitive control processes among individuals with OUD.

Summary

Individual differences in genetic and functional and structural brain-based features are correlated with differences in OUD severity and treatment outcomes, and therefore may potentially one day be used to inform OUD treatment selection. However, given the heterogeneous findings reported, further longitudinal research across different stages of opioid addiction is needed to yield a convergent characterization of OUD and improve treatment and prevention.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

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

  1. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. Arlington, VA: American Psychiatric Publishing; 2013.

  2. Hadland SE, Wharam JF, Schuster MA, Zhang F, Samet JH, Larochelle MR. Trends in receipt of buprenorphine and naltrexone for opioid use disorder among adolescents and young adults, 2001-2014. JAMA Pediatr. 2017;171(8):747–55.

    Article  PubMed  PubMed Central  Google Scholar 

  3. O'Donnell JK, Gladden RM, Seth P. Trends in deaths involving heroin and synthetic opioids excluding methadone, and law enforcement drug product reports, by census region - United States, 2006-2015. MMWR Morb Mortal Wkly Rep. 2017;66(34):897–903.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Schuckit MA. Treatment of opioid-use disorders. N Engl J Med. 2016;375(4):357–68.

    Article  PubMed  Google Scholar 

  5. Bart G. Maintenance medication for opiate addiction: the Foundation of Recovery. J Addict Dis. 2012;31(3):207–25.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Dugosh K, Abraham A, Seymour B, McLoyd K, Chalk M, Festinger D. A systematic review on the use of psychosocial interventions in conjunction with medications for the treatment of opioid addiction. J Addict Med. 2016;10(2):91–101.

    Article  CAS  PubMed Central  Google Scholar 

  7. Kouimtsidis C, Reynolds M, Coulton S, Drummond C. How does cognitive behaviour therapy work with opioid-dependent clients? Results of the UKCBTMM study. Drugs: Educ Prev Polic. 2012;19(3):253–8.

  8. Carroll KM, Ball SA, Martino S, Nich C, Babuscio TA, Nuro KF, et al. Computer-assisted delivery of cognitive-behavioral therapy for addiction: a randomized trial of CBT4CBT. Am J Psychiatry. 2008;165(7):881–8.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Hser YI, Mooney LJ, Saxon AJ, Miotto K, Bell DS, Zhu Y, et al. High mortality among patients with opioid use disorder in a large healthcare system. J Addict Med. 2017;11(4):315–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Hendershot CS, Witkiewitz K, George WH, Marlatt GA. Relapse prevention for addictive behaviors. Subst Abuse Treat Prev Policy. 2011;6:17.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Weiss RD, Potter JS, Fiellin DA, Byrne M, Connery HS, Dickinson W, et al. Adjunctive counseling during brief and extended buprenorphine-naloxone treatment for prescription opioid dependence: a 2-phase randomized controlled trial. Arch Gen Psychiatry. 2011;68(12):1238–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Woody GE, Poole SA, Subramaniam G, Dugosh K, Bogenschutz M, Abbott P, et al. Extended vs short-term buprenorphine-naloxone for treatment of opioid-addicted youth: a randomized trial. JAMA. 2008;300(17):2003–11.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Bertschy G. Methadone maintenance treatment: an update. Eur Arch Psychiatry Clin Neurosci. 1995;245(2):114–24.

    Article  CAS  PubMed  Google Scholar 

  14. Koob GF, Volkow ND. Neurocircuitry of addiction. Neuropsychopharmacology. 2010;35(1):217–38.

    Article  PubMed  Google Scholar 

  15. Abi-Dargham A, Horga G. The search for imaging biomarkers in psychiatric disorders. Nat Med. 2016;22(11):1248–55.

    Article  CAS  PubMed  Google Scholar 

  16. •• Darcq E, Kieffer BL. Opioid receptors: drivers to addiction? Nat Rev Neurosci. 2018;19(8):499–514 This review discusses the role of the opioid receptors in addiction and the translational potential of genetic, pharmacological and neuroimaging research in OUD.

    Article  CAS  PubMed  Google Scholar 

  17. Pert CB, Snyder SH. Properties of opiate-receptor binding in rat brain. Proc Natl Acad Sci. 1973;70(8):2243–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Lord JA, Waterfield AA, Hughes J, Kosterlitz HW. Endogenous opioid peptides: multiple agonists and receptors. Nature. 1977;267(5611):495–9.

    Article  CAS  PubMed  Google Scholar 

  19. Benarroch EE. Endogenous opioid systems: current concepts and clinical correlations. Neurology. 2012;79(8):807–14.

    Article  PubMed  Google Scholar 

  20. Al-Hasani R, Bruchas MR. Molecular mechanisms of opioid receptor-dependent signaling and behavior. Anesthesiology. 2011;115(6):1363–81.

    CAS  PubMed  Google Scholar 

  21. Toll L, Bruchas MR, Cox BM, Zaveri NT. Nociceptin/orphanin FQ receptor structure, signaling, ligands, functions, and interactions with opioid systems. Pharmacol Rev. 2016;68(2):419–57.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Mansour A, Hoversten MT, Taylor LP, Watson SJ, Akil H. The cloned mu, delta and kappa receptors and their endogenous ligands: evidence for two opioid peptide recognition cores. Brain Res. 1995;700(1–2):89–98.

    Article  CAS  PubMed  Google Scholar 

  23. Peng J, Sarkar S, Chang SL. Opioid receptor expression in human brain and peripheral tissues using absolute quantitative real-time RT-PCR. Drug Alcohol Depend. 2012;124(3):223–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Raynor K, Kong H, Chen Y, Yasuda K, Yu L, Bell GI, et al. Pharmacological characterization of the cloned kappa-, delta-, and mu-opioid receptors. Mol Pharmacol. 1994;45(2):330–4.

    CAS  PubMed  Google Scholar 

  25. Fields HL, Margolis EB. Understanding Opioid Reward. Trends Neurosci. 2015;38(4):217–25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Le Merrer J, Becker JA, Befort K, Kieffer BL. Reward processing by the opioid system in the brain. Physiol Rev. 2009;89(4):1379–412.

    Article  PubMed  Google Scholar 

  27. Richards EM, Mathews DC, Luckenbaugh DA, Ionescu DF, Machado-Vieira R, Niciu MJ, et al. A randomized, placebo-controlled pilot trial of the delta opioid receptor agonist AZD2327 in anxious depression. Psychopharmacology. 2016;233(6):1119–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Ayanga D, Shorter D, Kosten TR. Update on pharmacotherapy for treatment of opioid use disorder. Expert Opin Pharmacother. 2016;17(17):2307–18.

    Article  CAS  PubMed  Google Scholar 

  29. Connery HS. Medication-assisted treatment of opioid use disorder: review of the evidence and future directions. Harv Rev Psychiatry. 2015;23(2):63–75.

    Article  PubMed  Google Scholar 

  30. Mattick RP, Breen C, Kimber J, Davoli M. Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. Cochrane Database Syst Rev. 2009;3:CD002209.

    Google Scholar 

  31. Mattick RP, Breen C, Kimber J, Davoli M. Buprenorphine maintenance versus placebo or methadone maintenance for opioid dependence. Cochrane Database Syst Rev. 2014;2:CD002207.

    Google Scholar 

  32. D'Onofrio G, O'Connor PG, Pantalon MV, Chawarski MC, Busch SH, Owens PH, et al. Emergency department-initiated buprenorphine/naloxone treatment for opioid dependence: a randomized clinical trial. JAMA. 2015;313(16):1636–44.

    Article  PubMed  PubMed Central  Google Scholar 

  33. • Jarvis BP, Holtyn AF, Subramaniam S, Tompkins DA, Oga EA, Bigelow GE, et al. Extended-release injectable naltrexone for opioid use disorder: a systematic review. Addiction. 2018;113(7):1188–209 This systematic review examined extended-release injectable naltrexone (XR-NTX) for opioid use disorder, with regards to induction and adherence rates to XR-NTX as well as its effect on opioid use outcomes.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Minozzi S, Amato L, Vecchi S, Davoli M, Kirchmayer U, Verster A. Oral naltrexone maintenance treatment for opioid dependence. Cochrane Database Syst Rev. 2011;4:CD001333.

    Google Scholar 

  35. Krupitsky E, Nunes EV, Ling W, Illeperuma A, Gastfriend DR, Silverman BL. Injectable extended-release naltrexone for opioid dependence: a double-blind, placebo-controlled, multicentre randomised trial. Lancet. 2011;377(9776):1506–13.

    Article  CAS  PubMed  Google Scholar 

  36. • Tanum L, Solli KK, Latif ZE, Benth JS, Opheim A, Sharma-Haase K, et al. Effectiveness of Injectable Extended-Release Naltrexone vs Daily Buprenorphine-Naloxone for Opioid Dependence: A Randomized Clinical Noninferiority Trial. JAMA Psychiatry. 2017;74(12):1197–205 This randomized clinical trial demonstrates that injectable extended-release naltrexone is as effective as buprenorphine-naloxone in maintaining short-term abstinence from opioids.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Carroll KM, Nich C, Frankforter TL, Yip SW, Kiluk BD, DeVito EE, et al. Accounting for the uncounted: physical and affective distress in individuals dropping out of oral naltrexone treatment for opioid use disorder. Drug Alcohol Depend. 2018;192:264–70.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Samples H, Williams AR, Olfson M, Crystal S. Risk factors for discontinuation of buprenorphine treatment for opioid use disorders in a multi-state sample of Medicaid enrollees. J Subst Abus Treat. 2018;95:9–17.

    Article  Google Scholar 

  39. Berrettini W. A brief review of the genetics and pharmacogenetics of opioid use disorders. Dialogues Clin Neurosci. 2017;19(3):229–36.

    PubMed  PubMed Central  Google Scholar 

  40. Clarke TK, Weiss AR, Ferarro TN, Kampman KM, Dackis CA, Pettinati HM, et al. The dopamine receptor D2 (DRD2) SNP rs1076560 is associated with opioid addiction. Ann Hum Genet. 2014;78(1):33–9.

    Article  CAS  PubMed  Google Scholar 

  41. Bart G, Heilig M, LaForge K, Pollak L, Leal S, Ott J, et al. Substantial attributable risk related to a functional mu-opioid receptor gene polymorphism in association with heroin addiction in Central Sweden. Mol Psychiatry. 2004;9(6):547–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Drakenberg K, Nikoshkov A, Horváth MC, Fagergren P, Gharibyan A, Saarelainen K, et al. μ opioid receptor A118G polymorphism in association with striatal opioid neuropeptide gene expression in heroin abusers. Proc Natl Acad Sci. 2006;103(20):7883–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Coller JK, Beardsley J, Bignold J, Li Y, Merg F, Sullivan T, et al. Lack of association between the A118G polymorphism of the mu opioid receptor gene (OPRM1) and opioid dependence: a meta-analysis. Pharmacogenomics Pers Med. 2009;2:9–19.

    CAS  Google Scholar 

  44. Haerian BS, Haerian MS. OPRM1 rs1799971 polymorphism and opioid dependence: evidence from a meta-analysis. Pharmacogenomics. 2013;14(7):813–24.

    Article  CAS  PubMed  Google Scholar 

  45. Woodcock EA, Lundahl LH, Burmeister M, Greenwald MK. Functional mu opioid receptor polymorphism (OPRM1 A118G) associated with heroin use outcomes in Caucasian males: a pilot study. Am J Addict. 2015;24(4):329–35.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Crist RC, Clarke TK, Ang A, Ambrose-Lanci LM, Lohoff FW, Saxon AJ, et al. An intronic variant in OPRD1 predicts treatment outcome for opioid dependence in African-Americans. Neuropsychopharmacology. 2013;38(10):2003–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Clarke TK, Crist RC, Ang A, Ambrose-Lanci LM, Lohoff FW, Saxon AJ, et al. Genetic variation in OPRD1 and the response to treatment for opioid dependence with buprenorphine in European-American females. Pharmacogenomics J. 2014;14(3):303–8.

    Article  CAS  PubMed  Google Scholar 

  48. Crist RC, Doyle GA, Nelson EC, Degenhardt L, Martin NG, Montgomery GW, et al. A polymorphism in the OPRM1 3′-untranslated region is associated with methadone efficacy in treating opioid dependence. Pharmacogenomics J. 2016;18:173.

  49. • Smith AH, Jensen KP, Li J, Nunez Y, Farrer LA, Hakonarson H, et al. Genome-wide association study of therapeutic opioid dosing identifies a novel locus upstream of OPRM1. Mol Psychiatry. 2017;22(3):346–52 This genome-wide association study identified a significant association between methadone dose and a single nucleotide polymorphism closely located to the OPRM1 gene in African Americans, but not European Americans.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Wise RA, Koob GF. The development and maintenance of drug addiction. Neuropsychopharmacology. 2014;39(2):254–62.

    Article  PubMed  Google Scholar 

  51. Everitt BJ, Robbins TW. Neural systems of reinforcement for drug addiction: from actions to habits to compulsion. Nat Neurosci. 2005;8(11):1481–9.

    Article  CAS  PubMed  Google Scholar 

  52. Robinson TE, Berridge KC. The neural basis of drug craving: an incentive-sensitization theory of addiction. Brain Res Brain Res Rev. 1993;18(3):247–91.

    Article  CAS  PubMed  Google Scholar 

  53. Badiani A, Belin D, Epstein D, Calu D, Shaham Y. Opiate versus psychostimulant addiction: the differences do matter. Nat Rev Neurosci. 2011;12:685–700.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Ettenberg A, Pettit HO, Bloom FE, Koob GF. Heroin and cocaine intravenous self-administration in rats: mediation by separate neural systems. Psychopharmacology. 1982;78(3):204–9.

    Article  CAS  PubMed  Google Scholar 

  55. Avvisati R, Contu L, Stendardo E, Michetti C, Montanari C, Scattoni ML, et al. Ultrasonic vocalization in rats self-administering heroin and cocaine in different settings: evidence of substance-specific interactions between drug and setting. Psychopharmacology. 2016;233(8):1501–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. De Pirro S, Galati G, Pizzamiglio L, Badiani A. The affective and neural correlates of heroin vs. cocaine use in addiction are influenced by environmental setting but in opposite directions. Journal of Neuroscience. 2018;38(22):5182–95.

  57. Hartwell KJ, Back SE, McRae-Clark AL, Shaftman SR, Brady KT. Motives for using: a comparison of prescription opioid, marijuana and cocaine dependent individuals. Addict Behav. 2012;37(4):373–8.

    Article  PubMed  Google Scholar 

  58. Epstein DH, Willner-Reid J, Vahabzadeh M, Mezghanni M, Lin JL, Preston KL. Real-time electronic diary reports of cue exposure and mood in the hours before cocaine and heroin craving and use. Arch Gen Psychiatry. 2009;66(1):88–94.

    Article  PubMed  PubMed Central  Google Scholar 

  59. • Ahn W-Y, Vassileva J. Machine-learning identifies substance-specific behavioral markers for opiate and stimulant dependence. Drug Alcohol Depend. 2016;161:247–57 This study used a machine-learning approach to identify multivariate substance-specific markers that classify heroin and amphetamine dependence respectively.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Ahn WY, Ramesh D, Moeller FG, Vassileva J. Utility of machine-learning approaches to identify behavioral markers for substance use disorders: impulsivity dimensions as predictors of current cocaine dependence. Front Psychiatry. 2016;7:34.

    Article  PubMed  PubMed Central  Google Scholar 

  61. •• Moningka H, Lichenstein S, Worhunsky PD, DeVito EE, Scheinost D, Yip SW. Can neuroimaging help combat the opioid epidemic? A systematic review of clinical and pharmacological challenge fMRI studies with recommendations for future research. Neuropsychopharmacology. 2018;44:259–73. This is a systematic review of fMRI studies in opioid use disorder, including studies comparing opioid-dependent and healthy control participants as well as studies on opioid medications, treatment and abstinence effects.

  62. Li Q, Li W, Wang H, Wang Y, Zhang Y, Zhu J, et al. Predicting subsequent relapse by drug-related cue-induced brain activation in heroin addiction: an event-related functional magnetic resonance imaging study. Addict Biol. 2015;20(5):968–78.

    Article  CAS  PubMed  Google Scholar 

  63. Li Q, Yang WC, Wang YR, Huang YF, Li W, Zhu J, et al. Abnormal function of the posterior cingulate cortex in heroin addicted users during resting-state and drug-cue stimulation task. Chin Med J. 2013;126(4):734–9.

    PubMed  Google Scholar 

  64. Lou M, Wang E, Shen Y, Wang J. Cue-elicited craving in heroin addicts at different abstinent time: an fMRI pilot study. Subst Use Misuse. 2012;47(6):631–9.

    Article  PubMed  PubMed Central  Google Scholar 

  65. •• Volkow ND, Koob GF, McLellan AT. Neurobiologic Advances from the Brain Disease Model of Addiction. N Engl J Med. 2016;374(4):363–71 This article briefly summarizes current knowledge on neuroscience addiction research, including conceptual frameworks and neural circuitry underlying addiction.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Wang ZX, Zhang JX, Wu QL, Liu N, Hu XP, Chan RC, et al. Alterations in the processing of non-drug-related affective stimuli in abstinent heroin addicts. NeuroImage. 2010;49(1):971–6.

    Article  PubMed  Google Scholar 

  67. Zijlstra F, Veltman DJ, Booij J, van den Brink W, Franken IH. Neurobiological substrates of cue-elicited craving and anhedonia in recently abstinent opioid-dependent males. Drug Alcohol Depend. 2009;99(1–3):183–92.

    Article  PubMed  Google Scholar 

  68. Yip SW, DeVito EE, Kober H, Worhunsky PD, Carroll KM, Potenza MN. Anticipatory reward processing among cocaine-dependent individuals with and without concurrent methadone-maintenance treatment: relationship to treatment response(). Drug Alcohol Depend. 2016;166:134–42.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Gradin VB, Baldacchino A, Balfour D, Matthews K, Steele JD. Abnormal brain activity during a reward and loss task in opiate-dependent patients receiving methadone maintenance therapy. Neuropsychopharmacology. 2014;39(4):885–94.

    Article  CAS  PubMed  Google Scholar 

  70. Shi Z, Wang A-L, Jagannathan K, Fairchild VP, O’Brien CP, Childress AR, et al. Effects of extended-release naltrexone on the brain response to drug-related stimuli in patients with opioid use disorder. J Psychiatry Neurosci: JPN. 2018;43(4):254–61.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Wang A-L, Lowen SB, Elman I, Shi Z, Fairchild VP, Bouril A, et al. Sustained opioid antagonism modulates striatal sensitivity to baby schema in opioid use disorder. J Subst Abus Treat. 2018;85:70–7.

    Article  Google Scholar 

  72. Smoski MJ, Salsman N, Wang L, Smith V, Lynch TR, Dager SR, et al. Functional imaging of emotion reactivity in opiate-dependent borderline personality disorder. Personal Disord. 2011;2(3):230–41.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Schmidt A, Borgwardt S, Gerber H, Wiesbeck GA, Schmid O, Riecher-Rossler A, et al. Acute effects of heroin on negative emotional processing: relation of amygdala activity and stress-related responses. Biol Psychiatry. 2014;76(4):289–96.

    Article  CAS  PubMed  Google Scholar 

  74. Fu LP, Bi GH, Zou ZT, Wang Y, Ye EM, Ma L, et al. Impaired response inhibition function in abstinent heroin dependents: an fMRI study. Neurosci Lett. 2008;438(3):322–6.

    Article  CAS  PubMed  Google Scholar 

  75. Yucel M, Lubman DI, Harrison BJ, Fornito A, Allen NB, Wellard RM, et al. A combined spectroscopic and functional MRI investigation of the dorsal anterior cingulate region in opiate addiction. Mol Psychiatry. 2007;12(7):611 91-702.

    Article  CAS  PubMed  Google Scholar 

  76. Schmidt A, Walter M, Gerber H, Schmid O, Smieskova R, Bendfeldt K, et al. Inferior frontal cortex modulation with an acute dose of heroin during cognitive control. Neuropsychopharmacology. 2013;38(11):2231–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Sutherland MT, McHugh MJ, Pariyadath V, Stein EA. Resting state functional connectivity in addiction: lessons learned and a road ahead. NeuroImage. 2012;62(4):2281–95.

    Article  PubMed  Google Scholar 

  78. Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med. 1995;34(4):537–41.

    Article  CAS  PubMed  Google Scholar 

  79. Fox MD, Raichle ME. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci. 2007;8(9):700–11.

    Article  CAS  PubMed  Google Scholar 

  80. • Li Q, Liu J, Wang W, Wang Y, Li W, Chen J, et al. Disrupted coupling of large-scale networks is associated with relapse behaviour in heroin-dependent men. J Psychiatry Neurosci: JPN. 2018;43(1):48–57 This study investigated how resting-state functional connectivity among the salience, default mode and executive control networks correlate with heroin relapse behaviour.

    Article  PubMed  Google Scholar 

  81. Ma N, Liu Y, Li N, Wang C-X, Zhang H, Jiang X-F, et al. Addiction related alteration in resting-state brain connectivity. NeuroImage. 2010;49(1):738–44.

    Article  PubMed  Google Scholar 

  82. Upadhyay J, Maleki N, Potter J, Elman I, Rudrauf D, Knudsen J, et al. Alterations in brain structure and functional connectivity in prescription opioid-dependent patients. Brain. 2010;133(Pt 7):2098–114.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Wang PW, Lin HC, Liu GC, Yang YH, Ko CH, Yen CF. Abnormal interhemispheric resting state functional connectivity of the insula in heroin users under methadone maintenance treatment. Psychiatry Res Neuroimaging. 2016;255:9–14.

    Article  PubMed  Google Scholar 

  84. Menon V, Uddin LQ. Saliency, switching, attention and control: a network model of insula function. Brain Struct Funct. 2010;214(5–6):655–67.

    Article  PubMed  PubMed Central  Google Scholar 

  85. Dosenbach NU, Fair DA, Cohen AL, Schlaggar BL, Petersen SE. A dual-networks architecture of top-down control. Trends Cogn Sci. 2008;12(3):99–105.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. A default mode of brain function. Proc Natl Acad Sci U S A. 2001;98(2):676–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Corbetta M, Shulman GL. Control of goal-directed and stimulus-driven attention in the brain. Nat Rev Neurosci. 2002;3(3):201–15.

    Article  CAS  PubMed  Google Scholar 

  88. Fox MD, Zhang D, Snyder AZ, Raichle ME. The global signal and observed Anticorrelated resting state brain networks. J Neurophysiol. 2009;101(6):3270–83.

    Article  PubMed  PubMed Central  Google Scholar 

  89. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  90. Lerman C, Gu H, Loughead J, Ruparel K, Yang Y, Stein EA. Large-scale brain network coupling predicts acute nicotine abstinence effects on craving and cognitive function. JAMA Psychiatry. 2014;71(5):523–30.

    Article  PubMed  PubMed Central  Google Scholar 

  91. Li Q, Li Z, Li W, Zhang Y, Wang Y, Zhu J, et al. Disrupted default mode network and basal craving in male heroin-dependent individuals: a resting-state fMRI study. J Clin Psychiatry. 2016;77(10):e1211–e7.

    Article  PubMed  Google Scholar 

  92. Li W, Li Q, Wang D, Xiao W, Liu K, Shi L, et al. Dysfunctional default mode network in methadone treated patients who have a higher heroin relapse risk. Sci Rep. 2015;5:15181.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Wang W, Wang YR, Qin W, Yuan K, Tian J, Li Q, et al. Changes in functional connectivity of ventral anterior cingulate cortex in heroin abusers. Chin Med J. 2010;123(12):1582–8.

    PubMed  Google Scholar 

  94. Ma X, Qiu Y, Tian J, Wang J, Li S, Zhan W, et al. Aberrant default-mode functional and structural connectivity in heroin-dependent individuals. PLoS One. 2015;10(4):e0120861.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Yuan K, Qin W, Dong M, Liu J, Sun J, Liu P, et al. Gray matter deficits and resting-state abnormalities in abstinent heroin-dependent individuals. Neurosci Lett. 2010;482(2):101–5.

    Article  CAS  PubMed  Google Scholar 

  96. Liu J, Liang J, Qin W, Tian J, Yuan K, Bai L, et al. Dysfunctional connectivity patterns in chronic heroin users: an fMRI study. Neurosci Lett. 2009;460(1):72–7.

    Article  CAS  PubMed  Google Scholar 

  97. Xie C, Shao Y, Fu L, Goveas J, Ye E, Li W, et al. Identification of hyperactive intrinsic amygdala network connectivity associated with impulsivity in abstinent heroin addicts. Behav Brain Res. 2011;216(2):639–46.

    Article  PubMed  Google Scholar 

  98. Lyoo IK, Pollack MH, Silveri MM, Ahn KH, Diaz CI, Hwang J, et al. Prefrontal and temporal gray matter density decreases in opiate dependence. Psychopharmacology. 2006;184(2):139–44.

    Article  CAS  PubMed  Google Scholar 

  99. Yuan Y, Zhu Z, Shi J, Zou Z, Yuan F, Liu Y, et al. Gray matter density negatively correlates with duration of heroin use in young lifetime heroin-dependent individuals. Brain Cogn. 2009;71(3):223–8.

    Article  PubMed  Google Scholar 

  100. Y-w Q, G-h J, H-h S, X-f L, J-z T, L-m L, et al. The impulsivity behavior is correlated with prefrontal cortex gray matter volume reduction in heroin-dependent individuals. Neurosci Lett. 2013;538:43–8.

    Article  CAS  Google Scholar 

  101. Seifert CL, Magon S, Sprenger T, Lang UE, Huber CG, Denier N, et al. Reduced volume of the nucleus accumbens in heroin addiction. Eur Arch Psychiatry Clin Neurosci. 2015;265(8):637–45.

    Article  PubMed  Google Scholar 

  102. • Wollman SC, Alhassoon OM, Hall MG, Stern MJ, Connors EJ, Kimmel CL, et al. Gray matter abnormalities in opioid-dependent patients: A neuroimaging meta-analysis. The American Journal of Drug and Alcohol Abuse. 2017;43(5):505–17 This meta-analysis demonstrates that opioid-dependent individuals exhibited significantly decreased grey matter in fronto-cerebellar and fronto-insular regions compared to healthy individuals.

    Article  PubMed  Google Scholar 

  103. Wang X, Li B, Zhou X, Liao Y, Tang J, Liu T, et al. Changes in brain gray matter in abstinent heroin addicts. Drug Alcohol Depend. 2012;126(3):304–8.

    Article  CAS  PubMed  Google Scholar 

  104. Tolomeo S, Gray S, Matthews K, Steele J, Baldacchino A. Multifaceted impairments in impulsivity and brain structural abnormalities in opioid dependence and abstinence. Psychol Med. 2016;46(13):2841–53.

    Article  CAS  PubMed  Google Scholar 

  105. Qiu Y, Jiang G, Su H, Lv X, Zhang X, Tian J, et al. Progressive white matter microstructure damage in male chronic heroin dependent individuals: a DTI and TBSS study. PLoS One. 2013;8(5):e63212.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Bora E, Yücel M, Fornito A, Pantelis C, Harrison BJ, Cocchi L, et al. White matter microstructure in opiate addiction. Addict Biol. 2012;17(1):141–8.

    Article  CAS  PubMed  Google Scholar 

  107. Liu H, Li L, Hao Y, Cao D, Xu L, Rohrbaugh R, et al. Disrupted white matter integrity in heroin dependence: a controlled study utilizing diffusion tensor imaging. Am J Drug Alcohol Abuse. 2008;34(5):562–75.

    Article  PubMed  Google Scholar 

  108. Ivers JH, Fitzgerald J, Whelan C, Sweeney B, Keenan E, Fagan A, et al. Progressive white matter impairment as a predictor of outcome in a cohort of opioid-dependent patient's post-detoxification. Addict Biol. 2018;23(1):304–12.

    Article  CAS  PubMed  Google Scholar 

  109. Wollman SC, Alhassoon OM, Stern MJ, Hall MG, Rompogren J, Kimmel CL, et al. White matter abnormalities in long-term heroin users: a preliminary neuroimaging meta-analysis. Am J Drug Alcohol Abuse. 2015;41(2):133–8.

    Article  PubMed  Google Scholar 

  110. Wang Y, Li W, Li Q, Yang W, Zhu J, Wang W. White matter impairment in heroin addicts undergoing methadone maintenance treatment and prolonged abstinence: a preliminary DTI study. Neurosci Lett. 2011;494(1):49–53.

    Article  CAS  PubMed  Google Scholar 

  111. Li W, Zhu J, Li Q, Ye J, Chen J, Liu J, et al. Brain white matter integrity in heroin addicts during methadone maintenance treatment is related to relapse propensity. Brain and Behavior. 2016;6(2):e00436.

    Article  PubMed  PubMed Central  Google Scholar 

  112. Greicius MD, Supekar K, Menon V, Dougherty RF. Resting-state functional connectivity reflects structural connectivity in the default mode network. Cereb Cortex. 2009;19(1):72–8.

    Article  PubMed  Google Scholar 

  113. Dart RC, Surratt HL, Cicero TJ, Parrino MW, Severtson SG, Bucher-Bartelson B, et al. Trends in opioid analgesic abuse and mortality in the United States. N Engl J Med. 2015;372(3):241–8.

    Article  CAS  PubMed  Google Scholar 

  114. Pariyadath V, Gowin JL, Stein EA. Resting state functional connectivity analysis for addiction medicine: from individual loci to complex networks. Prog Brain Res. 2016;224:155–73.

    Article  PubMed  Google Scholar 

  115. Heilig M, Epstein DH, Nader MA, Shaham Y. Time to connect: bringing social context into addiction neuroscience. Nat Rev Neurosci. 2016;17(9):592–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Whelan R, Watts R, Orr CA, Althoff RR, Artiges E, Banaschewski T, et al. Neuropsychosocial profiles of current and future adolescent alcohol misusers. Nature. 2014;512(7513):185–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Yip SW, Scheinost D, Potenza MN, Carroll KM. Connectome-based prediction of cocaine abstinence. Am J Psychiatr. 2019. https://doi.org/10.1176/appi.ajp.2018.17101147.

Download references

Funding

This work was supported by NIDA grants T32 DA022975, K01DA039299 and R21DA045969.

Author information

Authors and Affiliations

  1. Department of Psychiatry, Yale School of Medicine, 1 Church Street, Suite 731, New Haven, CT, 06510, USA

    Hestia Moningka, Sarah Lichenstein & Sarah W. Yip

  2. Division of Psychology and Language Sciences, University College London, 26 Bedford Way, Bloomsbury, London, WC1H 0AP, UK

    Hestia Moningka

Authors
  1. Hestia Moningka
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sarah Lichenstein
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sarah W. Yip
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sarah W. Yip.

Ethics declarations

Conflict of Interest

Hestia Moningka, Sarah Lichenstein, and Sarah Yip declare no conflicts of interest relevant to this manuscript.

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.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Addictions

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Moningka, H., Lichenstein, S. & Yip, S.W. Current Understanding of the Neurobiology of Opioid Use Disorder: an Overview. Curr Behav Neurosci Rep 6, 1–11 (2019). https://doi.org/10.1007/s40473-019-0170-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40473-019-0170-4

Keywords

Search

Navigation