Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-26T09:01:34.939Z Has data issue: false hasContentIssue false
  • English
  • Français

Addiction as vulnerabilities in the decision process

Published online by Cambridge University Press:  29 July 2008

A. David Redish ,
Steve Jensen  and
Adam Johnson
A. David Redish
Affiliation:
Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455
Steve Jensen
Affiliation:
Graduate Program in Computer Science, University of Minnesota, Minneapolis, MN 55455
Adam Johnson
Affiliation:
Graduate Program in Neuroscience and Center for Cognitive Sciences, University of Minnesota, Minneapolis, MN 55455. [email protected]://umn.edu/~redish/[email protected]@umn.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

In our target article, we proposed that addiction could be envisioned as misperformance of a decision-making machinery described by two systems (deliberative and habit systems). Several commentators have argued that Pavlovian learning also produces actions. We agree and note that Pavlovian action-selection will provide several additional vulnerabilities. Several commentators have suggested that addiction arises from sociological parameters. We note in our response how sociological effects can change decision-making variables to provide additional vulnerabilities. Commentators generally have agreed that our theory provides a framework within which to site addiction and treatment, but additional work will be needed to determine whether our taxonomy will help identify and treat subpopulations within the addicted community.

Type
Authors' Response
Information
Behavioral and Brain Sciences , Volume 31 , Issue 4 , August 2008 , pp. 461 - 487
Copyright
Copyright © Cambridge University Press 2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Addolorato, G., Leggio, L., Abenavoli, L., Gasbarrini, G. & the Alcoholism Treatment Study Group (2005) Neurobiochemical and clinical aspects of craving in alcohol addiction: A review. Addictive Behaviors 30(6):1209–24.CrossRefGoogle ScholarPubMed
Ainslie, G. (1992) Picoeconomics: The strategic interaction of successive motivational states within the person. Cambridge University Press.Google Scholar
Ainslie, G. (2001) Breakdown of will. Cambridge University Press.Google Scholar
American Psychiatric Association (2000) Diagnostic and Statistical Manual of Mental Disorders, Text Revision (DSM-IV-TR™), 4thedition. American Psychiatric Association.Google Scholar
Andreou, C. (2005) Going from bad (or not so bad) to worse: On harmful addictions and habits. American Philosophical Quarterly 42(4):323–31.Google Scholar
Balleine, B. W. (2001) Incentive processes in instrumental conditioning. In: Handbook of contemporary learning theories, ed. Mowrer, R. R. & Klein, S. B., pp. 307–66. Erlbaum.Google Scholar
Balleine, B. W. (2004) Incentive behavior. In: The behavior of the laboratory rat: A handbook with tests, ed. Whishaw, I. Q. & Kolb, B., pp. 436–46. Oxford University Press.CrossRefGoogle Scholar
Balleine, B. W. & Ostlund, S. B. (2007) Still at the choice-point: Action selection and initiation in instrumental conditioning. Annals of the New York Academy of Sciences 1104:147–71.Google Scholar
Balster, R. L. (1973) Fixed-interval schedule of cocaine reinforcement: Effect of dose and infusion duration. Journal of Experimental Analysis of Behavior 20(1):119–29.CrossRefGoogle ScholarPubMed
Balster, R. L. (1988) Pharmacological effects of cocaine relevant to its abuse. In: Mechanisms of cocaine abuse and toxicity, ed. Clouet, D., Asghar, K. & Brown, R., pp. 1–13. National Institute on Drug Abuse.Google Scholar
Becker, G. S. (1976) The economic approach to human behavior. University of Chicago Press.CrossRefGoogle Scholar
Becker, G. S., Grossman, M. & Murphy, K. M. (1994) An empirical analysis of cigarette addiction. The American Economic Review 84(3):396–418.Google Scholar
Becker, G. S. & Murphy, K. M. (1988) A theory of rational addiction. Journal of Political Economy 96(4):675–700.CrossRefGoogle Scholar
Bell, D. E. (1982) Regret in decision making under uncertainty. Operations Research 30(5):961–82.CrossRefGoogle Scholar
Ben-Ari, M. (2005) Just a theory: Exploring the nature of science. Prometheus.Google Scholar
Berridge, K. C. (2007) The debate over dopamine's role in reward: The case for incentive salience. Psychopharmacology 191(3):391–431.CrossRefGoogle ScholarPubMed
Berridge, K. C. & Robinson, T. E. (2003) Parsing reward. Trends in Neurosciences 26(9):507–13.CrossRefGoogle ScholarPubMed
Breland, K. & Breland, M. (1961) The misbehavior of organisms. American Psychologist 16(11):682–84.CrossRefGoogle Scholar
Buckner, R. L. & Carroll, D. C. (2007) Self-projection and the brain. Trends in Cognitive Sciences 11(2):49–57.CrossRefGoogle ScholarPubMed
Caillé, S. & Parsons, L. H. (2003) SR141716A reduces the reinforcing properties of heroin but not heroin-induced increases in nucleus accumbens dopamine in rats. European Journal of Neuroscience 18(11):3145–49.Google Scholar
Carroll, K. M., Kosten, T. R. & Rounsaville, B. J. (2004) Choosing a behavioral therapy platform for pharmacotherapy of substance users. Drug and Alcohol Dependence 75(2):123–34.CrossRefGoogle ScholarPubMed
Carroll, M. E. (1993) The economic context of drug and non-drug reinforcers affects acquisition and maintenance of drug-reinforced behavior and withdrawal effects. Drug and Alcohol Dependence 33(2):201–10.Google Scholar
Carroll, M. E., Lac, S. T. & Nygaard, S. L. (1989) A concurrently available non-drug reinforcer prevents the acquisition or decreases the maintenance of cocaine-reinforced behavior. Psychopharmacology 97(1):23–29.CrossRefGoogle ScholarPubMed
Casey, B. J., Jones, R. M. & Hare, T. A. (2008) The adolescent brain. Annals of the New York Academy of Sciences 1124:111–26.CrossRefGoogle ScholarPubMed
Chambers, R. A., Bickel, W. K. & Potenza, M. N. (2007) A scale-free systems theory of motivation and addiction. Neuroscience and Biobehavioral Reviews 31(7):1017–45.CrossRefGoogle ScholarPubMed
Chambers, R. A., Taylor, J. R. & Potenza, M. N. (2003) Developmental neurocircuitry of motivation in adolescence: A critical period of addiction vulnerability. American Journal of Psychiatry 160(6):1041–52.CrossRefGoogle ScholarPubMed
Chiu, P. H., Lohrenz, T. M. & Montague, P. R. (2008) Smokers' brains compute, but ignore, a fictive error signal in a sequential investment task. Nature Neuroscience 11:514–20.CrossRefGoogle Scholar
Crabbe, J. C. (2002) Genetic contributions to addiction. Annual Review of Psychology 53(1):435–62.CrossRefGoogle ScholarPubMed
Daly, J. W. & Fredholm, B. B. (1998) Caffeine – an atypical drug of dependence. Drug and Alcohol Dependence 51:199–206.CrossRefGoogle ScholarPubMed
Daw, N. D. (2003) Reinforcement learning models of the dopamine system and their behavioral implications. Unpublished doctoral dissertation, Carnegie Mellon University, Pittsburgh, PA.Google Scholar
Daw, N. D., Kakade, S. & Dayan, P. (2002) Opponent interactions between serotonin and dopamine. Neural Networks 15:603–16.Google Scholar
Daw, N. D., Niv, Y. & Dayan, P. (2005) Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control. Nature Neuroscience 8:1704–11.Google Scholar
Dayan, P. & Balleine, B. W. (2002) Reward, motivation, and reinforcement learning. Neuron 36:285–98.CrossRefGoogle ScholarPubMed
Dayan, P., Niv, Y., Seymour, B. & Daw, N. D. (2006) The misbehavior of value and the discipline of the will. Neural Networks 19:1153–60.Google Scholar
Dickinson, A. (1980) Contemporary animal learning theory. Cambridge University Press.Google Scholar
Doya, K. (2000b) Reinforcement learning in continuous time and space. Neural Computation 12:219–45.Google Scholar
Elsmore, T. F., Fletcher, G. V., Conrad, D. G. & Sodetz, F. J. (1980) Reduction of heroin intake in baboons by an economic constraint. Pharmacology, Biochemistry and Behavior 13(5):729–31.Google Scholar
Everitt, B. J. & Robbins, T. W. (2005) Neural systems of reinforcement for drug addiction: From actions to habits to compulsion. Nature Neuroscience 8(11):1481–89.Google Scholar
Frank, M. J., Moustafa, A. A., Haughey, H. M., Curran, T. & Hutchison, K. E. (2007) Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning. Proceedings of the National Academy of Sciences 104(41):16311–16.CrossRefGoogle ScholarPubMed
Gilovich, T., Griffin, D. & Kahneman, D., eds. (2002) Heuristics and biases: The psychology of intuitive judgement. Cambridge University Press.CrossRefGoogle Scholar
Gold, M. S. (1997) Cocaine (and crack): Clinical aspects. In: Substance abuse: A comprehensive textbook, ed. Lowinson, J. H., Ruiz, P., Millman, R. B. & Langrod, J. G., pp. 181–99. Williams and Wilkins.Google Scholar
Goldman, M. S., Boca, F. K. D. & Darkes, J. (1999) Alcohol expectancy theory: The application of cognitive neuroscience. In: Psychological theories of drinking and alcoholism, ed. Leonard, K. E. & Blane, H. T., pp. 203–46. Guilford Press.Google Scholar
Goldman, M. S., Brown, S. A. & Christiansen, B. A. (1987) Expectancy theory: Thinking about drinking. In: Psychological theories of drinking and alcoholism, ed. Blaine, H. T. & Leonard, K. E., pp. 181–226. Guilford Press.Google Scholar
Grant, J. E., Potenza, M. N., Hollander, E., Cunningham-Williams, R., Nurminen, T., Smits, G. & Kallio, A. (2006) Multicenter investigation of the opioid antagonist nalmefene in the treatment of pathological gambling. American Journal of Psychiatry 163(2):303–12.CrossRefGoogle ScholarPubMed
Gray, J. A. & McNaughton, N. (2000) The neuropsychology of anxiety. Oxford University Press.Google Scholar
Graybiel, A. M. (1998) The basal ganglia and chunking of action repertoires. Neurobiology of Learning and Memory 70 (1–2):119–36.Google Scholar
Greden, J. F. & Walters, A. (1997) Caffeine. In: Substance abuse: A comprehensive textbook, ed. Lowinson, J. H., Ruiz, P., Millman, R. B. & Langrod, J. G., pp. 294–307. Williams and Wilkins.Google Scholar
Grossman, M. & Chaloupka, F. J. (1998) The demand for cocaine by young adults: A rational addiction approach. Journal of Health Economics 17:427–74.CrossRefGoogle ScholarPubMed
Hart, C. L., Haney, M., Foltin, R. W. & Fischman, M. W. (2000) Alternative reinforcers differentially modify cocaine self-administration by humans. Behavioral Pharmacology 11(1):87–91.Google Scholar
Hatsukami, D. K., Thompson, T. N., Pentel, P. R., Flygare, B. K. & Carroll, M. E. (1994) Self-administration of smoked cocaine. Experimental and Clinical Psychopharmacology 2(2):115–25.Google Scholar
Hemby, S., Martin, T., Co, C., Dworkin, S. & Smith, J. (1995) The effects of intravenous heroin administration on extracellular nucleus accumbens dopamine concentrations as determined by in vivo microdialysis. The Journal of Pharmacology and Experimental Therapeutics 273(2):591–98.Google Scholar
Henningfield, J. E. & Keenan, R. M. (1993) Nicotine delivery kinetics and abuse liability. Journal of Consulting and Clinical Psychology 61(5):743–50.Google Scholar
Higgins, S. T., Alessi, S. M. & Dantona, R. L. (2002) Voucher-based incentives: A substance abuse treatment innovation. Addictive Behaviors 27:887–910.CrossRefGoogle ScholarPubMed
Higgins, S. T., Heil, S. H. & Lussier, J. P. (2004) Clinical implications of reinforcement as a determinant of substance use disorders. Annual Review of Psychology 55(1):431–61.CrossRefGoogle ScholarPubMed
Holden, C. (2001) “Behavioral” addictions: Do they exist? Science 294:980–82.CrossRefGoogle ScholarPubMed
Husain, M., Parton, A., Hodgson, T. L., Mort, D. & Rees, G. (2003) Self-control during response conflict by human supplementary eye field. Nature Neuroscience 6:117–18.CrossRefGoogle ScholarPubMed
Hyman, S. E. (2005) Addiction: A disease of learning and memory. American Journal of Psychiatry 162:1414–22.CrossRefGoogle ScholarPubMed
Irvin, J. E. & Brandon, T. H. (2000) The increasing recalcitrance of smokers in clinical trials. Nicotine and Tobacco Research 2(1):79–84.Google ScholarPubMed
Irvin, J. E., Hendricks, P. S. & Brandon, T. H. (2003) The increasing recalcitrance of smokers in clinical trials: II. Pharmacotherapy trials. Nicotine and Tobacco Research 5(1):27–35.CrossRefGoogle ScholarPubMed
Isoda, M. & Hikosaka, O. (2007) Switching from automatic to controlled action by monkey medial frontal cortex. Nature Neuroscience 10:240–48.CrossRefGoogle ScholarPubMed
Iversen, S. D. & Mishkin, M. (1970) Perseverative interference in monkeys following selective lesions of the inferior prefrontal convexity. Experimental Brain Research 11(4):376–86.Google Scholar
Johnson, A. & Redish, A. D. (2007) Neural ensembles in CA3 transiently encode paths forward of the animal at a decision point. Journal of Neuroscience 27(45):12176–89.Google Scholar
Johnson, A., van, derMeer, M. A. A. & Redish, A. D. (2007) Integrating hippocampus and striatum in decision-making. Current Opinion in Neurobiology 17(6):692–97.CrossRefGoogle ScholarPubMed
Kahneman, D. & Frederick, S. (2002) Representativeness revisited: Attribute substitution in intuitive judgment. In: Heuristics and biases: The psychology of intuitive judgment, ed. Gilovich, T., Griffin, D. & Kahneman, D., pp. 49–81. Cambridge University Press.Google Scholar
Kahneman, D. & Tversky, A. (1979) Prospect theory: An analysis of decision under risk. Econometrica 47(2):263–92.Google Scholar
Kalivas, P. W., Peters, J. & Knackstedt, L. (2006) Animal models and brain circuits in drug addiction. Molecular Interventions 6:339–44.CrossRefGoogle ScholarPubMed
Kelley, A. E., Schochet, T. & Landry, C. F. (2004) Risk taking and novelty seeking in adolescence: Introduction to part I. Annals of the New York Academy of Sciences 1021:27–32.CrossRefGoogle ScholarPubMed
Kiyatkin, E. A. & Rebec, G. V. (1997) Activity of presumed dopamine neurons in the ventral tegmental area during heroin self-administration. NeuroReport 8(11):2581–85.CrossRefGoogle ScholarPubMed
Kiyatkin, E. A. & Rebec, G. V. (2001) Impulse activity of ventral tegmental area neurons during heroin self-administration in rats. Neuroscience 102(3):565–80.Google Scholar
Koob, G. F. & Le Moal, M. (2006) Neurobiology of addiction. Elsevier Academic.Google Scholar
Laviolette, S. R., Gallegos, R. A., Henriksen, S. J. & van, derKooy, D. (2004) Opiate state controls bi-directional reward signaling via GABAA receptors in the ventral tegmental area. Nature Neuroscience 7(2):160–69.CrossRefGoogle ScholarPubMed
Lee, D. (2008) Game theory and neural basis of social decision making. Nature Neuroscience 11:404–409.Google Scholar
Lenoir, M. & Ahmed, S. H. (2007) Supply of a nondrug substitute reduces escalated heroin consumption. Neuropsychopharmacology. (doi:10.1038/sj.npp.1301602)Google Scholar
Lenoir, M., Serre, F., Cantin, L. & Ahmed, S. H. (2007) Intense sweetness surpasses cocaine reward. PLoS ONE 2(8):e698.Google Scholar
Leshner, A. I. (1997) Addiction is a brain disease, and it matters. Science 278(5335):45–47.Google Scholar
Liu, J.-L., Liu, J.-T., Hammit, J. K. & Chou, S.-Y. (1999) The price elasticity of opium in Taiwan, 1914–1942. Journal of Health Economics 18:795–810.Google Scholar
Lohrenz, T., McCabe, K., Camerer, C. F. & Montague, P. R. (2007) Neural signature of fictive learning signals in a sequential investment task. Proceedings of the National Academy of Sciences USA 104(22):9493–98.CrossRefGoogle Scholar
Mackintosh, N. J. (1974) The psychology of animal learning. Academic Press.Google Scholar
Mayr, E. (1998) This is biology: The science of the living world. Belknap.Google Scholar
Meyer, R. & Mirin, S. (1979) The heroin stimulus. Plenum.CrossRefGoogle Scholar
Montague, P. R., Dayan, P., Person, C. & Sejnowski, T. J. (1995) Bee foraging in uncertain environments using predictive Hebbian learning. Nature 377(6551):725–28.Google Scholar
Montague, P. R., Dayan, P. & Sejnowski, T. J. (1996) A framework for mesencephalic dopamine systems based on predictive Hebbian learning. Journal of Neuroscience 16(5):1936–47.CrossRefGoogle ScholarPubMed
Nader, M. A. & Woolverton, W. L. (1990) Cocaine vs. food choice in rhesus monkeys: Effects of increasing the response cost for cocaine. NIDA Research Monographs 105:621.Google Scholar
Nader, M. A. & Woolverton, W. L. (1991) Effects of increasing the magnitude of an alternative reinforcer on drug choice in a discrete-trials choice procedure. Psychopharmacology 105:169–74.CrossRefGoogle Scholar
Nestler, E. J. (2005) Is there a common molecular pathway for addiction? Nature Neuroscience 8:1445–49.Google Scholar
Newell, A. (1990) Unified theories of cognition. Harvard University Press.Google Scholar
Niv, Y. (2006) The effects of motivation on habitual instrumental behavior. Unpublished doctoral dissertation, Interdisciplinary Center for Neural Computation, The Hebrew University of Jerusalem.Google Scholar
Niv, Y. (2007) Cost, benefit, tonic, phasic. What do response rates tell us about dopamine and motivation? Annals of the New York Academy of Sciences 1104(1):357–76.Google Scholar
Niv, Y., Daw, N. D. & Dayan, P. (2006a) How fast to work: Response vigor, motivation and tonic dopamine. In: Advances in neural information processing systems 18, ed. Weiss, Y., Schölkopf, B. & Platt, J., pp. 1019–26. MIT Press.Google Scholar
Niv, Y., Joel, D. & Dayan, P. (2006b) A normative perspective on motivation. Trends in Cognitive Sciences 10(8):375–81.CrossRefGoogle ScholarPubMed
Niv, Y., Daw, N. D., Joel, D. & Dayan, P. (2007) Tonic dopamine: Opportunity costs and the control of response vigor. Psychopharmacology 191(3):507–20.Google Scholar
Nurnberger, J. I. & Bierut, L. (2007) Seeking the connections: Alcoholism and our genes. Scientific American 296(4):46–53.Google Scholar
O'Brien, C. P. & McLellan, A. T. (1996) Myths about the treatment of addiction. The Lancet 347:237–40.Google Scholar
O'Brien, C. P., Volkow, N. & Li, T.-K. (2006) What's in a word? Addiction versus dependence in DSM-V. American Journal of Psychiatry 163:764–65.Google Scholar
O'Brien, C. P., Volpicelli, L. A. & Volpicelli, J. R. (1996) Naltrexone in the treatment of alcoholism: A clinical review. Alcohol 13(1):35–39.Google Scholar
O'Donoghue, T. & Rabin, M. (1999a) Doing it now or later. The American Economic Review 89(1):103–23.Google Scholar
Padoa-Schioppa, C. & Assad, J. A. (2006) Neurons in the orbitofrontal cortex encode economic value. Nature 441:223–26.Google Scholar
Paulus, M. P. (2007) Decision-making dysfunctions in psychiatry – altered homeostatic processing? Science 318(5850):602–606.Google Scholar
Potenza, M. N. (2006) Should addictive disorders include non-substance-related conditions? Addiction 101(S1):142–51.Google Scholar
Potenza, M. N., Kosten, T. R. & Rounsaville, B. J. (2001) Pathological gambling. Journal of the American Medical Association 286(2):141–44.Google Scholar
Rachlin, H. (2004) The science of self-control. Harvard University Press.Google Scholar
Ramus, S. J., Davis, J. B., Donahue, R. J., Discenza, C. B. & Waite, A. A. (2007) Interactions between the orbitofrontal cortex and hippocampal memory system during the storage of long-term memory. Annals of the New York Academy of Sciences 1121:216–31.Google Scholar
Redish, A. D. (2004) Addiction as a computational process gone awry. Science 306(5703):1944–47.Google Scholar
Redish, A. D., Jensen, S., Johnson, A. & Kurth-Nelson, Z. (2007) Reconciling reinforcement learning models with behavioral extinction and renewal: Implications for addiction, relapse, and problem gambling. Psychological Review 114(3):784–805.Google Scholar
Redish, A. D. & Johnson, A. (2007) A computational model of craving and obsession. Annals of the New York Academy of Sciences 1104(1):324–39.Google Scholar
Reynolds, B. R., Ortengren, A., Richards, J. B. & de Wit, H. (2006) Dimensions of impulsive behavior: Personality and behavioral measures. Personality and Individual Differences 40(2):305–15.Google Scholar
Roberts, W. A., Feeney, M. C., Macpherson, K., Petter, M., McMillan, N. & Musolino, E. (2008) Episodic-like memory in rats: Is it based on when or how long ago? Science 320(5872):113–15.Google Scholar
Robinson, T. E. & Berridge, K. C. (2003) Addiction. Annual Reviews of Psychology 54(1):25–53.Google Scholar
Rocha, B. A., Fumagalli, F., Gainetdinov, R. R., Jones, S. R., Ator, R., Giros, B., Miller, G. W. & Caron, M. G. (1998) Cocaine self-administration in dopamine-transporter knockout mice. Nature Neuroscience 1(2):132–37.Google Scholar
Sakagami, M., Pan, X. & Uttl, B. (2006) Behavioral inhibition and prefrontal cortex in decision-making. Neural Networks 19(8):1255–65.Google Scholar
Sayette, M. A., Shiffman, S., Tiffany, S. T., Niaura, R. S., Martin, C. S. & Shadel, W. G. (2000) The measurement of drug craving. Addiction 95 (Suppl. 2):S189–S210.Google Scholar
Schacter, D. L. (2001) The seven sins of memory. Houghton Mifflin.Google Scholar
Schacter, D. L. & Tulving, E., eds. (1994) Memory systems 1994. MIT Press.Google Scholar
Schoenbaum, G., Roesch, M. & Stalnaker, T. A. (2006a) Orbitofrontal cortex, decision making, and drug addiction. Trends in Neurosciences 29(2):116–24.Google Scholar
Schultz, W. (1998) Predictive reward signal of dopamine neurons. Journal of Neurophysiology 80:1–27.CrossRefGoogle ScholarPubMed
Sharpe, L. (2002) A reformulated cognitive-behavioral model of problem gambling: A biopsychosocial perspective. Clinical Psychology Review 22(1):1–25.CrossRefGoogle ScholarPubMed
Simon, H. (1955) A behavioral model of rational choice. The Quarterly Journal of Economics 69:99–118.Google Scholar
Stephens, D. W. & Krebs, J. R. (1987) Foraging theory. Princeton.CrossRefGoogle Scholar
Suddendorf, T. & Busby, J. (2003) Mental time travel in animals? Trends in Cognitive Sciences 7(9):391–96.Google Scholar
Suri, R. E. (2002) TD models of reward predictive responses in dopamine neurons. Neural Networks 15:523–33.Google Scholar
Sutton, R. S. & Barto, A. G. (1998) Reinforcement learning: An introduction. MIT Press.Google Scholar
Tiffany, S. T. (1990) A cognitive model of drug urges and drug-use behavior: Role of automatic and nonautomatic processes. Psychological Review 97(2):147–68.Google Scholar
Volkow, N. D., Fowler, J. S. & Wang, G.-J. (2002) Role of dopamine in drug reinforcement and addiction in humans: Results from imaging studies. Behavioral Pharmacology 13(5):355–66.Google Scholar
Windmann, S., Kirsch, P., Mier, D., Stark, R., Walter, B., Gunturkun, O. & Vaitl, D. (2006) On framing effects in decision making: Linking lateral versus medial orbitofrontal cortex activation to choice outcome processing. Journal of Cognitive Neuroscience 18(7):1198–211.CrossRefGoogle ScholarPubMed
Wise, R. A., Leone, P., Rivest, R. & Leeb, K. (1995) Elevations of nucleus accumbens dopamine and DOPAC levels during intravenous heroin self-administration. Synapse 21:140–48.Google Scholar
Wood, W. & Neal, D. T. (2007) A new look at habits and the habit-goal interface. Psychological Review 114:843–63.Google Scholar
World Health Organization (1992) International classification of diseases, ICD-10. World Health Organization.Google Scholar
Xi, Z.-X., Fuller, S. A. & Stein, E. A. (1998) Dopamine release in the nucleus accumbens during heroin self-administration is modulated by kappa opioid receptors: An in vivo fast-cyclic voltammetry study. The Journal of Pharmacology and Experimental Therapeutics 284(1):151–61.Google Scholar
Zilli, E. A. & Hasselmo, M. E. (2008) Modeling the role of working memory and episodic memory in behavioral tasks. Hippocampus 18(2):193–209.Google Scholar