Skip to main content

Advertisement

SpringerLink
Log in

Toward an Understanding of Dynamic Moral Decision Making: Model-Free and Model-Based Learning

  • Published:
Journal of Business Ethics Aims and scope Submit manuscript

Abstract

In business settings, decision makers facing moral issues often experience the challenges of continuous changes. This dynamic process has been less examined in previous literature on moral decision making. We borrow theories on learning strategies and computational models from decision neuroscience to explain the updating and learning mechanisms underlying moral decision processes. Specifically, we present two main learning strategies: model-free learning, wherein the values of choices are updated in a trial-and-error fashion sustaining the formation of habits and model-based learning, wherein the brain updates more general cognitive maps and associations, thus sustaining flexible and state-dependent behaviors. We then summarize studies explaining the neuro-computational processes of both learning strategies—the calculation of prediction errors and valuation. We conclude by emphasizing how the incorporation of dynamic aspects in moral decision making could open new avenues for understanding moral behaviors in a changing world.

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
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. Notice that in this context, the term “value” refers to the magnitude of outcome and should not be confused with other interpretations such as social values etc.

  2. The concept of utility here is more generic than the way is used by “Utilitarian” approaches.

Abbreviations

DN:

Decision neuroscience

RPE:

Reward prediction error

SPE:

State prediction error

VMPFC:

Ventro-medial prefrontac cortex

SMH:

Somatic marker hypothesis

DLPFC:

Dorso lateral prefrontal cortex

References

  • Abbink, K., Irlenbusch, B., & Renner, E. (2002). An experimental bribery game. Journal of Law Economics and Organization, 18(2), 428–454.

    Article  Google Scholar 

  • Aharon, I., Etcoff, N., Ariely, D., Chabris, C. F., O’Connor, E., & Breiter, H. C. (2001). Beautiful faces have variable reward value: fMRI and behavioral evidence. Neuron, 32(3), 537–551.

    Article  Google Scholar 

  • Aimone, J. A., Houser, D., & Weber, B. (2014). Neural signatures of betrayal aversion: An fMRI study of trust. Proceedings of the Royal Society B: Biological Sciences, 281(1782), 20132127.

    Article  Google Scholar 

  • Alessi, S., & Petry, N. (2003). Pathological gambling severity is associated with impulsivity in a delay discounting procedure. Behavioural Processes, 64(3), 345–354.

    Article  Google Scholar 

  • Anderson, S. W., Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (1999). Impairment of social and moral behavior related to early damage in human prefrontal cortex. Nature Neuroscience, 2(11), 1032–1037.

    Article  Google Scholar 

  • Ariely, D., Bracha, A., & Meier, S. (2009). Doing good or doing well? Image motivation and monetary incentives in behaving prosocially. American Economic Review, 99(1), 544–555.

    Article  Google Scholar 

  • Baker, F., Johnson, M. W., & Bickel, W. K. (2003). Delay discounting in current and never-before cigarette smokers: Similarities and differences across commodity, sign, and magnitude. Journal of Abnormal Psychology, 112(3), 382.

    Article  Google Scholar 

  • Ballard, K., Knutson, B. (2009). Dissociable neural representations of future reward magnitude and delay during temporal discounting. NeuroImage, 45, 143–150.

    Article  Google Scholar 

  • Bayer, J., Bandurski, P., & Sommer, T. (2013). Differential modulation of activity related to the anticipation of monetary gains and losses across the menstrual cycle. European Journal of Neuroscience, 38(10), 3519–3526.

    Article  Google Scholar 

  • Bayer, H. M., & Glimcher, P. W. (2005). Midbrain dopamine neurons encode a quantitative reward prediction error signal. Neuron, 47(1), 129–141.

    Article  Google Scholar 

  • Bechara, A., & Damasio, H. (2002). Decision-making and addiction (part I): Impaired activation of somatic states in substance dependent individuals when pondering decisions with negative future consequences. Neuropsychologia, 40(10), 1675–1689.

    Article  Google Scholar 

  • Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (2005). The Iowa Gambling Task and the somatic marker hypothesis: Some questions and answers. Trends in cognitive sciences, 9(4), 159–162. discussion 162–154.

    Article  Google Scholar 

  • Behrens, T. E., Hunt, L. T., Woolrich, M. W., & Rushworth, M. F. (2008). Associative learning of social value. Nature, 456(7219), 245–249.

    Article  Google Scholar 

  • Beierholm, U. R., Anen, C., Quartz, S., & Bossaerts, P. (2011). Separate encoding of model-based and model-free valuations in the human brain. Neuroimage, 58(3), 955–962.

    Article  Google Scholar 

  • Bickel, W. K., Odum, A. L., & Madden, G. J. (1999). Impulsivity and cigarette smoking: Delay discounting in current, never, and ex-smokers. Psychopharmacology (Berl), 146(4), 447–454.

    Article  Google Scholar 

  • Bickel, W. K., Pitcock, J. A., Yi, R., & Angtuaco, E. J. (2009). Congruence of BOLD response across intertemporal choice conditions: Fictive and real money gains and losses. Journal of Neuroscience, 29(27), 8839–8846.

    Article  Google Scholar 

  • Bossaerts, P. (2009). What decision neuroscience teaches us about financial decision making. Annual Review of Financial Economics, 1, 383–404.

    Article  Google Scholar 

  • Burke, C. J., & Tobler, P. N. (2011). Reward skewness coding in the insula independent of probability and loss. Journal of Neurophysiology, 106(5), 2415–2422.

    Article  Google Scholar 

  • Burke, C. J., Tobler, P. N., Baddeley, M., & Schultz, W. (2010). Neural mechanisms of observational learning. Proceedings of the National Academy of Sciences of the United States of America, 107(32), 14431–14436.

    Article  Google Scholar 

  • Camerer, C. F. (2008). Neuroeconomics: Opening the gray box. Neuron, 60(3), 416–419.

    Article  Google Scholar 

  • Carver, C. S., & Scheier, M. F. (1982). Control-theory: A useful conceptual-framework for personality-social, clinical, and health psychology. Psychological Bulletin, 92(1), 111–135.

    Article  Google Scholar 

  • Christopoulos, G., & Hong, Y. Y. (2013). Turning two uninvited guests into prominent speakers: Toward a dynamic culture neuroscience. Psychological Inquiry, 24(1), 20–25.

    Article  Google Scholar 

  • Christopoulos, G. I., & King-Casas, B. (2015). With you or against you: Social orientation dependent learning signals guide actions made for others. Neuroimage, 104, 326–335.

    Article  Google Scholar 

  • Christopoulos, G., Kokkinaki, F., Harvey, N., & Sevdalis, N. (2011). Paying for no reason? (Mis-) perceptions of product attributes in separate vs. joint product evaluation. Journal of Economic Psychology, 32(5), 857–864.

    Article  Google Scholar 

  • Christopoulos, G. I., Tobler, P. N., Bossaerts, P., Dolan, R. J., & Schultz, W. (2009). Neural correlates of value, risk, and risk aversion contributing to decision making under risk. The Journal of neuroscience: The Official Journal of the Society for Neuroscience, 29(40), 12574–12583.

    Article  Google Scholar 

  • Chung, D., Christopoulos, G. I., King-Casas, B., Ball, S. B., & Chiu, P. H. (2015). Social signals of safety and risk confer utility and have asymmetric effects on observers’ choices. Nature Neuroscience, 18(6), 912–916.

    Article  Google Scholar 

  • Cohen, J. D., & Aston-Jones, G. (2005). Cognitive neuroscience: Decision amid uncertainty. Nature, 436(7050), 471–472.

    Article  Google Scholar 

  • Cole, M., & Packer, M. (2015). A bio-cultural-historical approach to the study of development. In M. J. Gelfand, C. Y. Chiu, & Y. Y. Hong (Eds.), Advances in culture and psychology (Vol. 6). New York: Oxford University Press.

    Google Scholar 

  • Cushman, F., Young, L., & Hauser, M. (2006). The role of conscious reasoning and intuition in moral judgment: Testing three principles of harm. Psychological Science, 17(12), 1082–1089.

    Article  Google Scholar 

  • Damasio, A. R. (1996). The somatic marker hypothesis and the possible functions of the prefrontal cortex. Philosophical Transactions of the Royal Society of London. Series B, Biological sciences, 351(1346), 1413–1420.

    Article  Google Scholar 

  • Daw, N. D. (2012). Model-based reinforcement learning as cognitive search: Neurocomputational theories. In P. M. Todd & T. R. Robbins (Eds.), Cognitive search: Evolution, algorithms and the brain. Cambridge: MIT Press.

    Google Scholar 

  • Daw, N. D., & Doya, K. (2006). The computational neurobiology of learning and reward. Current Opinion in Neurobiology, 16(2), 199–204.

    Article  Google Scholar 

  • Daw, N. D., Gershman, S. J., Seymour, B., Dayan, P., & Dolan, R. J. (2011). Model-based influences on humans’ choices and striatal prediction errors. Neuron, 69(6), 1204–1215.

    Article  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(12), 1704–1711.

    Article  Google Scholar 

  • Dayan, P., & Daw, N. D. (2008). Decision theory, reinforcement learning, and the brain. Cognitive, Affective, & Behavioral Neuroscience, 8(4), 429–453.

    Article  Google Scholar 

  • Dayan, P., Niv, Y., Seymour, B., & Daw, N. D. (2006). The misbehavior of value and the discipline of the will. Neural Networks, 19(8), 1153–1160.

    Article  Google Scholar 

  • de Araujo, I. E., Kringelbach, M. L., Rolls, E. T., & McGlone, F. (2003). Human cortical responses to water in the mouth, and the effects of thirst. Journal of Neurophysiology, 90(3), 1865–1876.

    Article  Google Scholar 

  • de Araujo, I. E., Rolls, E. T., Velazco, M. I., Margot, C., & Cayeux, I. (2005). Cognitive modulation of olfactory processing. Neuron, 46(4), 671–679.

    Article  Google Scholar 

  • de Wit, H., Enggasser, J. L., & Richards, J. B. (2002). Acute administration of d-amphetamine decreases impulsivity in healthy volunteers. Neuropsychopharmacology, 27(5), 813–825.

    Article  Google Scholar 

  • Decety, J., Jackson, P. L., Sommerville, J. A., Chaminade, T., & Meltzoff, A. N. (2004). The neural bases of cooperation and competition: An fMRI investigation. Neuroimage, 23(2), 744–751.

    Article  Google Scholar 

  • Delgado, M. R., Frank, R. H., & Phelps, E. A. (2005a). Perceptions of moral character modulate the neural systems of reward during the trust game. Nature Neuroscience, 8(11), 1611–1618.

    Article  Google Scholar 

  • Delgado, M. R., Miller, M. M., Inati, S., & Phelps, E. A. (2005b). An fMRI study of reward-related probability learning. Neuroimage, 24(3), 862–873.

    Article  Google Scholar 

  • Deserno, L., Huys, Q. J. M., Boehme, R., Buchert, R., Heinze, H. J., Grace, A. A., et al. (2015). Ventral striatal dopamine reflects behavioral and neural signatures of model-based control during sequential decision making. Proceedings of the National Academy of Sciences of the United States of America, 112(5), 1595–1600.

    Article  Google Scholar 

  • Doya, K. (2002). Metalearning and neuromodulation. Neural Networks, 15(4–6), 495–506.

    Article  Google Scholar 

  • Doya, K., Samejima, K., Katagiri, K., & Kawato, M. (2002). Multiple model-based reinforcement learning. Neural Computation, 14(6), 1347–1369.

    Article  Google Scholar 

  • Dreher, J. C., & Burnod, Y. (2002). An integrative theory of the phasic and tonic modes of dopamine modulation in the prefrontal cortex. Neural Networks, 15(4–6), 583–602.

    Article  Google Scholar 

  • Du, W., Green, L., & Myerson, J. (2002). Cross-cultural comparisons of discounting delayed and probabilistic rewards. Psychological Record, 52(4), 479–492.

    Article  Google Scholar 

  • Fehr, E., Fischbacher, U., & Kosfeld, M. (2005). Neuroeconomic foundations of trust and social preferences: Initial evidence. American Economic Review, 95(2), 346–351.

    Article  Google Scholar 

  • Fermin, A., Yoshida, T., Ito, M., Yoshimoto, J., & Doya, K. (2010). Evidence for model-based action planning in a sequential finger movement task. Journal of Motor Behavior, 42(6), 371–379.

    Article  Google Scholar 

  • Fisher, H., Aron, A., & Brown, L. L. (2005). Romantic love: An fMRI study of a neural mechanism for mate choice. Journal of Comparative Neurology, 493(1), 58–62.

    Article  Google Scholar 

  • Fliessbach, K., Weber, B., Trautner, P., Dohmen, T., Sunde, U., Elger, C. E., & Falk, A. (2007). Social comparison affects reward-related brain activity in the human ventral striatum. Science, 318(5854), 1305–1308.

    Article  Google Scholar 

  • Frederick, S., Loewenstein, G., & O’Donoghue, T. (2002). Time discounting and time preference: A critical review. Journal of Economic Literature, 40(2), 351–401.

    Article  Google Scholar 

  • Fuster, A., & Meier, S. (2010). Another hidden cost of incentives: The detrimental effect on norm enforcement. Management Science, 56(1), 57–70.

    Article  Google Scholar 

  • Garrett, T. A., & Sobel, R. S. (1999). Gamblers favor skewness, not risk: Further evidence from United States’ lottery games. Economics Letters, 63(1), 85–90.

    Article  Google Scholar 

  • Gillan, C. M., Otto, A. R., Phelps, E. A., & Daw, N. D. (2015). Model-based learning protects against forming habits. Cognitive, Affective, & Behavioral Neuroscience, 15, 523.

    Article  Google Scholar 

  • Gillan, C. M., Papmeyer, M., Morein-Zamir, S., Sahakian, B. J., Fineberg, N. A., Robbins, T. W., & de Wit, S. (2011). Disruption in the balance between goal-directed behavior and habit learning in obsessive-compulsive disorder. American Journal of Psychiatry, 168(7), 718–726.

    Article  Google Scholar 

  • Glascher, J., Daw, N., Dayan, P., & O’Doherty, J. P. (2010). States versus rewards: Dissociable neural prediction error signals underlying model-based and model-free reinforcement learning. Neuron, 66(4), 585–595.

    Article  Google Scholar 

  • Glimcher, P. W., Dorris, M. C., & Bayer, H. M. (2005). Physiological utility theory and the neuroeconomics of choice. Games and Economic Behavior, 52(2), 213–256.

    Article  Google Scholar 

  • Glimcher, P. W., & Fehr, E. (2013). Neuroeconomics: Decision making and the brain. London: Academic Press.

    Google Scholar 

  • Gneezy, U., Meier, S., & Rey-Biel, P. (2011). When and why incentives (Don’t) work to modify behavior. Journal of Economic Perspectives, 25(4), 191–209.

    Article  Google Scholar 

  • Gneezy, U., & Rustichini, A. (2000). A fine is a price. Journal of Legal Studies, 29(1), 1–17.

    Article  Google Scholar 

  • Gong, M., Baron, J., & Kunreuther, H. (2009). Group cooperation under uncertainty. Journal of Risk and Uncertainty, 39(3), 251–270.

    Article  Google Scholar 

  • Green, L., Fry, A. F., & Myerson, J. (1994). Discounting of delayed rewards: A life-span comparison. Psychological Science, 5(1), 33–36.

    Article  Google Scholar 

  • Greene, J. D. (2007). Why are VMPFC patients more utilitarian? A dual-process theory of moral judgment explains. Trends in Cognitive Sciences, 11(8), 322–323. author reply 323–324.

    Article  Google Scholar 

  • Greene, J. D. (2009). The cognitive neuroscience of moral judgment. The Cognitive Neurosciences, 4, 987–999.

    Google Scholar 

  • Greene, J. D., Cushman, F. A., Stewart, L. E., Lowenberg, K., Nystrom, L. E., & Cohen, J. D. (2009). Pushing moral buttons: The interaction between personal force and intention in moral judgment. Cognition, 111(3), 364–371.

    Article  Google Scholar 

  • Haidt, J. (2001). The emotional dog and its rational tail: A social intuitionist approach to moral judgment. Psychological Review, 108(4), 814–834.

    Article  Google Scholar 

  • Haidt, J. (2007). The new synthesis in moral psychology. Science, 316(5827), 998–1002.

    Article  Google Scholar 

  • Haruno, M., & Kawato, M. (2006). Different neural correlates of reward expectation and reward expectation error in the putamen and caudate nucleus during stimulus-action-reward association learning. Journal of Neurophysiology, 95(2), 948–959.

    Article  Google Scholar 

  • Harvey, A. H., Kirk, U., Denfield, G. H., & Montague, P. R. (2010). Monetary favors and their influence on neural responses and revealed preference. Journal of Neuroscience, 30(28), 9597–9602.

    Article  Google Scholar 

  • Heil, S. H., Johnson, M. W., Higgins, S. T., & Bickel, W. K. (2006). Delay discounting in currently using and currently abstinent cocaine-dependent outpatients and non-drug-using matched controls. Addictive Behaviors, 31(7), 1290–1294.

    Article  Google Scholar 

  • Hollerman, J. R., Tremblay, L., & Schultz, W. (1998). Influence of reward expectation on behavior-related neuronal activity in primate striatum. Journal of Neurophysiology, 80(2), 947–963.

    Google Scholar 

  • Hong, Y. Y. (2008). Dynamic constructivist approach to culture. International Journal of Psychology, 43(3–4), 421–422.

    Google Scholar 

  • Huettel, S. A., Song, A. W., & McCarthy, G. (2005). Decisions under uncertainty: Probabilistic context influences activation of prefrontal and parietal cortices. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 25(13), 3304–3311.

    Article  Google Scholar 

  • Ikeda, S., Kang, M.-I., & Ohtake, F. (2010). Hyperbolic discounting, the sign effect, and the body mass index. Journal of Health Economics, 29(2), 268–284.

    Article  Google Scholar 

  • Illes, J., & Bird, S. J. (2006). Neuroethics: A modern context for ethics in neuroscience. Trends in Neurosciences, 29(9), 511–517.

    Article  Google Scholar 

  • Izuma, K., Saito, D. N., & Sadato, N. (2008). Processing of social and monetary rewards in the human striatum. Neuron, 58(2), 284–294.

    Article  Google Scholar 

  • Jiang, T., Soussignan, R., Schaal, B., & Royet, J. P. (2014). Reward for food odors: An fMRI study of liking and wanting as a function of metabolic state and BMI. Social Cognitive and Affective Neuroscience.

  • Jones, T. M. (1991). Ethical decision-making by individuals in organizations: An issue-contingent model. Academy of Management Review, 16(2), 366–395.

    Google Scholar 

  • Kahneman, D., & Frederick, S. (2002). Representativeness revisited: Attribute substitution in intuitive judgment. Heuristics and biases: The psychology of intuitive judgment, 49

  • Kahneman, D., & Frederick, S. (2005). A model of heuristic judgment. In The Cambridge handbook of thinking and reasoning. Cambridge: Cambridge University Press, pp 267–293.

  • Kahneman, D., & Tversky, A. (1979). Prospect theory: Analysis of decision under risk. Econometrica, 47(2), 263–291.

    Article  Google Scholar 

  • King-Casas, B., Tomlin, D., Anen, C., Camerer, C. F., Quartz, S. R., & Montague, P. R. (2005). Getting to know you: Reputation and trust in a two-person economic exchange. Science, 308(5718), 78–83.

    Article  Google Scholar 

  • Knutson, B., Wimmer, G. E., Kuhnen, C. M., & Winkielman, P. (2008). Nucleus accumbens activation mediates the influence of reward cues on financial risk taking. NeuroReport, 19(5), 509–513.

    Article  Google Scholar 

  • Kringelbach, M. L., O’Doherty, J., Rolls, E. T., & Andrews, C. (2003). Activation of the human orbitofrontal cortex to a liquid food stimulus is correlated with its subjective pleasantness. Cerebral Cortex, 13(10), 1064–1071.

    Article  Google Scholar 

  • Krueger, F., McCabe, K., Moll, J., Kriegeskorte, N., Zahn, R., Strenziok, M., et al. (2007). Neural correlates of trust. Proceedings of the National Academy of Sciences of the United States of America, 104(50), 20084–20089.

    Article  Google Scholar 

  • Kuhnen, C. M., & Knutson, B. (2005). The neural basis of financial risk taking. Neuron, 47(5), 763–770.

    Article  Google Scholar 

  • Kunreuther, H., Silvasi, G., Bradlow, E. T., & Small, D. (2009). Bayesian analysis of deterministic and stochastic prisoner’s dilemma games. Judgment and Decision Making, 4(5), 363–384.

    Google Scholar 

  • Lacey, S., Hagtvedt, H., Patrick, V. M., Anderson, A., Stilla, R., Deshpande, G., et al. (2011). Art for reward’s sake: Visual art recruits the ventral striatum. Neuroimage, 55(1), 420–433.

    Article  Google Scholar 

  • Lauharatanahirun, N., Christopoulos, G. I., & King-Casas, B. (2012). Neural computations underlying social risk sensitivity. Frontiers in Human Neuroscience, 6, 213.

    Article  Google Scholar 

  • Lawrence, N. S., Hinton, E. C., Parkinson, J. A., & Lawrence, A. D. (2012). Nucleus accumbens response to food cues predicts subsequent snack consumption in women and increased body mass index in those with reduced self-control. Neuroimage, 63(1), 415–422.

    Article  Google Scholar 

  • Lee, S. W., Shimojo, S., & O’Doherty, J. P. (2014). Neural computations underlying arbitration between model-based and model-free learning. Neuron, 81(3), 687–699.

    Article  Google Scholar 

  • Lieberman, M. D., Gaunt, R., Gilbert, D. T., & Trope, Y. (2002). Reflexion and reflection: A social cognitive neuroscience approach to attributional inference. Advances in Experimental Social Psychology, 34(34), 199–249.

    Article  Google Scholar 

  • Loewenstein, G. (1987). Anticipation and the valuation of delayed consumption. Economic Journal, 97(387), 666–684.

    Article  Google Scholar 

  • Loewenstein, G. F. (1988). Frames of mind in intertemporal choice. Management Science, 34(2), 200–214.

    Article  Google Scholar 

  • Loewenstein, G., & O’Donoghue, T. (2004). Animal spirits: Affective and deliberative processes in economic behavior. Available at SSRN 539843.

  • McClure, S. M., Berns, G. S., & Montague, P. R. (2003). Temporal prediction errors in a passive learning task activate human striatum. Neuron, 38(2), 339–346.

    Article  Google Scholar 

  • McClure, S. M., Li, J., Tomlin, D., Cypert, K. S., Montague, L. M., & Montague, P. R. (2004). Neural correlates of behavioral preference for culturally familiar drinks. Neuron, 44(2), 379–387.

    Article  Google Scholar 

  • McCoy, A. N., & Platt, M. L. (2005). Expectations and outcomes: Decision-making in the primate brain. Journal of Comparative Physiology A Neuroethology, Sensory, Neural, and Behavioral Physiology, 191(3), 201–211.

    Article  Google Scholar 

  • Mischel, W., Grusec, J., & Masters, J. C. (1969). Effects of expected delay time on subjective value of rewards and punishments. Journal of Personality and Social Psychology, 11(4), 363–373.

    Article  Google Scholar 

  • Miyapuram, K. P., & Pammi, V. S. (2013). Understanding decision neuroscience: A multidisciplinary perspective and neural substrates. Progress in Brain Research, 202, 239–266.

    Article  Google Scholar 

  • Miyapuram, K. P., Tobler, P. N., Gregorios-Pippas, L., & Schultz, W. (2012). BOLD responses in reward regions to hypothetical and imaginary monetary rewards. Neuroimage, 59(2), 1692–1699.

    Article  Google Scholar 

  • Moll, J., & de Oliveira-Souza, R. (2007). Response to Greene: Moral sentiments and reason: Friends or foes? Trends in Cognitive Sciences, 11(8), 323.

    Article  Google Scholar 

  • Moll, J., de Oliveira-Souza, R., Bramati, I. E., & Grafman, J. (2002a). Functional networks in emotional moral and nonmoral social judgments. Neuroimage, 16(3 Pt 1), 696–703.

    Article  Google Scholar 

  • Moll, J., de Oliveira-Souza, R., Eslinger, P. J., Bramati, I. E., Mourao-Miranda, J., Andreiuolo, P. A., & Pessoa, L. (2002b). The neural correlates of moral sensitivity: A functional magnetic resonance imaging investigation of basic and moral emotions. Journal of Neuroscience, 22(7), 2730–2736.

    Google Scholar 

  • Moll, J., Eslinger, P. J., & Oliveira-Souza, R. (2001). Frontopolar and anterior temporal cortex activation in a moral judgment task: Preliminary functional MRI results in normal subjects. Arq Neuropsiquiatr, 59(3-B), 657–664.

    Article  Google Scholar 

  • Montague, P. R., Dolan, R. J., Friston, K. J., & Dayan, P. (2012). Computational psychiatry. Trends in Cognitive Sciences, 16(1), 72–80.

    Article  Google Scholar 

  • Montague, P. R., Harvey, A. H., & Kirk, U. (2014). Using fMRI to study valuation and choice.

  • Montague, P. R., & King-Casas, B. (2007). Efficient statistics, common currencies and the problem of reward-harvesting. Trends in cognitive sciences, 11(12), 514–519.

    Article  Google Scholar 

  • Mulder, L. B., & Aquino, K. (2013). The role of moral identity in the aftermath of dishonesty. Organizational Behavior and Human Decision Processes, 121(2), 219–230.

    Article  Google Scholar 

  • Odum, A. L. (2011). Delay discounting: Trait variable? Behavioural Processes, 87(1), 1–9.

    Article  Google Scholar 

  • Odum, A. L., Madden, G. J., & Bickel, W. K. (2002). Discounting of delayed health gains and losses by current, never- and ex-smokers of cigarettes. Nicotine & Tobacco Research, 4(3), 295–303.

    Article  Google Scholar 

  • Osuch, E. A., Bluhm, R. L., Williamson, P. C., Theberge, J., Densmore, M., & Neufeld, R. W. (2009). Brain activation to favorite music in healthy controls and depressed patients. NeuroReport, 20(13), 1204–1208.

    Article  Google Scholar 

  • Paloyelis, Y., Asherson, P., Mehta, M. A., Faraone, S. V., & Kuntsi, J. (2010). DAT1 and COMT effects on delay discounting and trait impulsivity in male adolescents with attention deficit/hyperactivity disorder and healthy controls. Neuropsychopharmacology, 35(12), 2414–2426.

    Article  Google Scholar 

  • Pavlov, I. P. (2003). Conditioned reflexes. New York: Courier Corporation.

    Google Scholar 

  • Pessiglione, M., Seymour, B., Flandin, G., Dolan, R. J., & Frith, C. D. (2006). Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans. Nature, 442(7106), 1042–1045.

    Article  Google Scholar 

  • Plassmann, H., O’Doherty, J., & Rangel, A. (2007). Orbitofrontal cortex encodes willingness to pay in everyday economic transactions. Journal of Neuroscience, 27(37), 9984–9988.

    Article  Google Scholar 

  • Platt, M. L., & Huettel, S. A. (2008). Risky business: The neuroeconomics of decision making under uncertainty. Nature Neuroscience, 11(4), 398–403.

    Article  Google Scholar 

  • Preuschoff, K., Quartz, S. R., & Bossaerts, P. (2008). Human insula activation reflects risk prediction errors as well as risk. Journal of Neuroscience, 28(11), 2745–2752.

    Article  Google Scholar 

  • Rangel, A., Camerer, C., & Montague, P. R. (2008). A framework for studying the neurobiology of value-based decision making. Nature Reviews Neuroscience, 9(7), 545–556.

    Article  Google Scholar 

  • Reynolds, S. J. (2006). A neurocognitive model of the ethical decision-making process: Implications for study and practice. Journal of Applied Psychology, 91(4), 737–748.

    Article  Google Scholar 

  • Rilling, J., Gutman, D., Zeh, T., Pagnoni, G., Berns, G., & Kilts, C. (2002). A neural basis for social cooperation. Neuron, 35(2), 395–405.

    Article  Google Scholar 

  • Robertson, D., Snarey, J., Ousley, O., Harenski, K., DuBois Bowman, F., Gilkey, R., & Kilts, C. (2007). The neural processing of moral sensitivity to issues of justice and care. Neuropsychologia, 45(4), 755–766.

    Article  Google Scholar 

  • Roberts, A. C., Christopoulos, G. I., Car, J., Soh, C. K., & Lu, M. (2016). Psycho-biological factors associated with underground spaces: What can the new era of cognitive neuroscience offer to their study? Tunnelling and Underground Space Technology.

  • Rothschild, M., & Stiglitz, J. E. (1970). Increasing Risk. 1. Definition. Journal of Economic Theory, 2(3), 225–243.

    Article  Google Scholar 

  • Sanfey, A. G. (2007). Social decision-making: Insights from game theory and neuroscience. Science, 318(5850), 598–602.

    Article  Google Scholar 

  • Schonberg, T., Daw, N. D., Joel, D., & O’Doherty, J. P. (2007). Reinforcement learning signals in the human striatum distinguish learners from nonlearners during reward-based decision making. Journal of Neuroscience, 27(47), 12860–12867.

    Article  Google Scholar 

  • Schultz, W. (2008). Introduction. Neuroeconomics: The promise and the profit. Philosophical Transactions of the Royal Society of London. Series B, Biological sciences, 363(1511), 3767–3769.

    Article  Google Scholar 

  • Schultz, W., Dayan, P., & Montague, P. R. (1997). A neural substrate of prediction and reward. Science, 275(5306), 1593–1599.

    Article  Google Scholar 

  • Schultz, W., Preuschoff, K., Camerer, C., Hsu, M., Fiorillo, C. D., Tobler, P. N., & Bossaerts, P. (2008). Explicit neural signals reflecting reward uncertainty. Philosophical Transactions of the Royal Society of London. Series B, Biological sciences, 363(1511), 3801–3811.

    Article  Google Scholar 

  • Schultz, W., Tremblay, L., & Hollerman, J. R. (1998). Reward prediction in primate basal ganglia and frontal cortex. Neuropharmacology, 37(4–5), 421–429.

    Article  Google Scholar 

  • Schultz, W., Tremblay, L., & Hollerman, J. R. (2003). Changes in behavior-related neuronal activity in the striatum during learning. Trends in Neurosciences, 26(6), 321–328.

    Article  Google Scholar 

  • Small, D. M., Gregory, M. D., Mak, Y. E., Gitelman, D., Mesulam, M. M., & Parrish, T. (2003). Dissociation of neural representation of intensity and affective valuation in human gustation. Neuron, 39(4), 701–711.

    Article  Google Scholar 

  • Smith, D. V., & Huettel, S. A. (2010). Decision neuroscience: Neuroeconomics. Wiley Interdisciplinary Reviews: Cognitive Science, 1(6), 854–871.

    Google Scholar 

  • Spinella, M., Lester, D., & Yang, B. (2004). Gambling and delaying rewards as a function of frontal system dysfunction: A study in neuroeconomics. Perceptual and Motor Skills, 99(3 Pt 1), 993–994.

    Article  Google Scholar 

  • Steinberg, L., Graham, S., O’Brien, L., Woolard, J., Cauffman, E., & Banich, M. (2009). Age differences in future orientation and delay discounting. Child Development, 80(1), 28–44.

    Article  Google Scholar 

  • Sutton, R., & Barto, A. (1988). Reinforcement learning: An introduction. Cambridge: MIT Press.

    Google Scholar 

  • Suzuki, S., Harasawa, N., Ueno, K., Gardner, J. L., Ichinohe, N., Haruno, M., et al. (2012). Learning to simulate others’ decisions. Neuron, 74(6), 1125–1137.

    Article  Google Scholar 

  • Symmonds, M., Wright, N. D., Bach, D. R., & Dolan, R. J. (2011). Deconstructing risk: Separable encoding of variance and skewness in the brain. Neuroimage, 58(4), 1139–1149.

    Article  Google Scholar 

  • Tanaka, S. C., Yamada, K., Yoneda, H., & Ohtake, F. (2014). Neural mechanisms of gain-loss asymmetry in temporal discounting. Journal of Neuroscience, 34(16), 5595–5602.

    Article  Google Scholar 

  • Thaler, R. (1981a). Some empirical-evidence on dynamic inconsistency. Economics Letters, 8(3), 201–207.

    Article  Google Scholar 

  • Thaler, R. H. (1981b). Maximization and self-control. Behavioral and Brain Sciences, 4(3), 403–404.

    Article  Google Scholar 

  • Thorndike, E. L. (1911). Animal intelligence: Experimental studies. New York: Macmillan.

    Book  Google Scholar 

  • Tobler, P. N., Christopoulos, G. I., O’Doherty, J. P., Dolan, R. J., & Schultz, W. (2008a). Neuronal distortions of reward probability without choice. Journal of Neuroscience, 28(45), 11703–11711.

    Article  Google Scholar 

  • Tobler, P. N., Kalis, A., & Kalenscher, T. (2008b). The role of moral utility in decision making: An interdisciplinary framework. Cognitive, Affective, & Behavioral Neuroscience, 8(4), 390–401.

    Article  Google Scholar 

  • Tolman, E. C. (1948). Cognitive maps in rats and men. Psychological Review, 55(4), 189–208.

    Article  Google Scholar 

  • Venkatraman, V. (2013). Why bother with the brain? A role for decision neuroscience in understanding strategic variability. Progress in Brain Research, 202, 267–288.

    Article  Google Scholar 

  • Voon, V., Derbyshire, K., Ruck, C., Irvine, M. A., Worbe, Y., Enander, J., et al. (2015). Disorders of compulsivity: A common bias towards learning habits. Molecular Psychiatry, 20(3), 345–352.

    Article  Google Scholar 

  • Winstanley, C. A., Dalley, J. W., Theobald, D. E., & Robbins, T. W. (2003). Global 5-HT depletion attenuates the ability of amphetamine to decrease impulsive choice on a delay-discounting task in rats. Psychopharmacology (Berl), 170(3), 320–331.

    Article  Google Scholar 

  • Wunderlich, K., Dayan, P., & Dolan, R. J. (2012a). Mapping value based planning and extensively trained choice in the human brain. Nature Neuroscience, 15(5), 786–791.

    Article  Google Scholar 

  • Wunderlich, K., Smittenaar, P., & Dolan, R. J. (2012b). Dopamine enhances model-based over model-free choice behavior. Neuron, 75(3), 418–424.

    Article  Google Scholar 

  • Yates, J. F., & Watts, R. A. (1975). Preferences for deferred losses. Organizational Behavior and Human Performance, 13(2), 294–306.

    Article  Google Scholar 

  • Young, L., & Koenigs, M. (2007). Investigating emotion in moral cognition: A review of evidence from functional neuroimaging and neuropsychology. British Medical Bulletin, 84, 69–79.

    Article  Google Scholar 

  • Zink, C. F., Pagnoni, G., Martin-Skurski, M. E., Chappelow, J. C., & Berns, G. S. (2004). Human striatal responses to monetary reward depend on saliency. Neuron, 42(3), 509–517.

    Article  Google Scholar 

  • Zink, C. F., Tong, Y., Chen, Q., Bassett, D. S., Stein, J. L., & Meyer-Lindenberg, A. (2008). Know your place: Neural processing of social hierarchy in humans. Neuron, 58(2), 273–283.

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to thank the Editors as well as two anonymous reviewers for their constructive comments in an earlier version of this paper. The preparation of this article was partially supported by the Academic Research Fund (AcRF) Tier 2 (MOE2012-T2-1-051) of the Ministry of Education, Singapore, awarded to Ying-yi Hong and George Christopoulos and by the Academic Research Fund (AcRF) Tier 1 (RG 1/11 M4010946.010) of the Ministry of Education, Singapore, awarded to the first author.

Author information

Authors and Affiliations

  1. Nanyang Business School, Nanyang Technological University, S3-B2B-64, 50 Nanyang Avenue, Singapore, 639798, Singapore

    George I. Christopoulos

  2. Culture Science Institute, Nanyang Technological University, S3-B3-C, 50 Nanyang Avenue, Singapore, 639798, Singapore

    George I. Christopoulos

  3. The Chinese University of Hong Kong, Hong-Kong, China

    Ying-yi Hong

  4. Department of Business Management, School of Management, Xiamen University, Xiamen, China

    Xiao-Xiao Liu

Authors
  1. George I. Christopoulos
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiao-Xiao Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ying-yi Hong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to George I. Christopoulos, Xiao-Xiao Liu or Ying-yi Hong.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Christopoulos, G.I., Liu, XX. & Hong, Yy. Toward an Understanding of Dynamic Moral Decision Making: Model-Free and Model-Based Learning. J Bus Ethics 144, 699–715 (2017). https://doi.org/10.1007/s10551-016-3058-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10551-016-3058-1

Keywords

Search

Navigation