Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Moral transgressions corrupt neural representations of value

Abstract

Moral systems universally prohibit harming others for personal gain. However, we know little about how such principles guide moral behavior. Using a task that assesses the financial cost participants ascribe to harming others versus themselves, we probed the relationship between moral behavior and neural representations of profit and pain. Most participants displayed moral preferences, placing a higher cost on harming others than themselves. Moral preferences correlated with neural responses to profit, where participants with stronger moral preferences had lower dorsal striatal responses to profit gained from harming others. Lateral prefrontal cortex encoded profit gained from harming others, but not self, and tracked the blameworthiness of harmful choices. Moral decisions also modulated functional connectivity between lateral prefrontal cortex and the profit-sensitive region of dorsal striatum. The findings suggest moral behavior in our task is linked to a neural devaluation of reward realized by a prefrontal modulation of striatal value representations.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Figure 1: Moral decision task and behavioral results.
Figure 2: Moral transgressions modulate corticostriatal responses to profit.
Figure 3: Blame computation in LPFC.
Figure 4: Corticostriatal connectivity during the exercise of moral choices.

References

  1. Gert, B. Common Morality: Deciding What to Do (Oxford University Press, 2004).

  2. Smith, A. The Theory of Moral Sentiments (Penguin, 2010).

  3. Boehm, C. Moral Origins: The Evolution of Virtue, Altruism, and Shame (Basic Books, 2012).

  4. Rand, D.G. & Epstein, Z.G. Risking your life without a second thought: intuitive decision-making and extreme altruism. PLoS One 9, e109687 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Marsh, A.A. et al. Neural and cognitive characteristics of extraordinary altruists. Proc. Natl. Acad. Sci. USA 111, 15036–15041 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Greene, J.D. in The Cognitive Neurosciences V 1013–1023 (MIT Press, 2014).

  7. FeldmanHall, O. et al. Differential neural circuitry and self-interest in real vs hypothetical moral decisions. Soc. Cogn. Affect. Neurosci. 7, 743–751 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  8. FeldmanHall, O., Dalgleish, T., Evans, D. & Mobbs, D. Empathic concern drives costly altruism. Neuroimage 105, 347–356 (2015).

    Article  PubMed  Google Scholar 

  9. Greene, J.D. & Paxton, J.M. Patterns of neural activity associated with honest and dishonest moral decisions. Proc. Natl. Acad. Sci. USA 106, 12506–12511 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Yu, H., Hu, J., Hu, L. & Zhou, X. The voice of conscience: neural bases of interpersonal guilt and compensation. Soc. Cogn. Affect. Neurosci. 9, 1150–1158 (2014).

    Article  PubMed  Google Scholar 

  11. Morishima, Y., Schunk, D., Bruhin, A., Ruff, C.C. & Fehr, E. Linking brain structure and activation in temporoparietal junction to explain the neurobiology of human altruism. Neuron 75, 73–79 (2012).

    Article  CAS  PubMed  Google Scholar 

  12. Hutcherson, C.A., Bushong, B. & Rangel, A. A neurocomputational model of altruistic choice and its implications. Neuron 87, 451–462 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Hare, T.A., Camerer, C.F., Knoepfle, D.T. & Rangel, A. Value computations in ventral medial prefrontal cortex during charitable decision making incorporate input from regions involved in social cognition. J. Neurosci. 30, 583–590 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Hein, G., Silani, G., Preuschoff, K., Batson, C.D. & Singer, T. Neural responses to ingroup and outgroup members' suffering predict individual differences in costly helping. Neuron 68, 149–160 (2010).

    Article  CAS  PubMed  Google Scholar 

  15. Crockett, M.J., Kurth-Nelson, Z., Siegel, J.Z., Dayan, P. & Dolan, R.J. Harm to others outweighs harm to self in moral decision making. Proc. Natl. Acad. Sci. USA 111, 17320–17325 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Crockett, M.J. et al. Dissociable effects of serotonin and dopamine on the valuation of harm in moral decision-making. Curr. Biol. 25, 1852–1859 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Stellar, J.E. & Willer, R. The corruption of value negative moral associations diminish the value of money. Soc. Psychol. Personal. Sci. 5, 60–66 (2014).

    Article  Google Scholar 

  18. Zaki, J. & Ochsner, K.N. The neuroscience of empathy: progress, pitfalls and promise. Nat. Neurosci. 15, 675–680 (2012).

    Article  CAS  PubMed  Google Scholar 

  19. Lamm, C., Decety, J. & Singer, T. Meta-analytic evidence for common and distinct neural networks associated with directly experienced pain and empathy for pain. Neuroimage 54, 2492–2502 (2011).

    Article  PubMed  Google Scholar 

  20. Bartra, O., McGuire, J.T. & Kable, J.W. The valuation system: a coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value. Neuroimage 76, 412–427 (2013).

    Article  PubMed  Google Scholar 

  21. Clithero, J.A. & Rangel, A. Informatic parcellation of the network involved in the computation of subjective value. Soc. Cogn. Affect. Neurosci. 9, 1289–1302 (2014).

    Article  PubMed  Google Scholar 

  22. Rangel, A. & Hare, T. Neural computations associated with goal-directed choice. Curr. Opin. Neurobiol. 20, 262–270 (2010).

    Article  CAS  PubMed  Google Scholar 

  23. Buckholtz, J.W. & Marois, R. The roots of modern justice: cognitive and neural foundations of social norms and their enforcement. Nat. Neurosci. 15, 655–661 (2012).

    Article  CAS  PubMed  Google Scholar 

  24. Spitzer, M., Fischbacher, U., Herrnberger, B., Grön, G. & Fehr, E. The neural signature of social norm compliance. Neuron 56, 185–196 (2007).

    Article  CAS  PubMed  Google Scholar 

  25. Ruff, C.C., Ugazio, G. & Fehr, E. Changing social norm compliance with noninvasive brain stimulation. Science 342, 482–484 (2013).

    Article  CAS  PubMed  Google Scholar 

  26. Chang, L.J., Smith, A., Dufwenberg, M. & Sanfey, A.G. Triangulating the neural, psychological, and economic bases of guilt aversion. Neuron 70, 560–572 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Baumgartner, T., Knoch, D., Hotz, P., Eisenegger, C. & Fehr, E. Dorsolateral and ventromedial prefrontal cortex orchestrate normative choice. Nat. Neurosci. 14, 1468–1474 (2011).

    Article  CAS  PubMed  Google Scholar 

  28. Buckholtz, J.W. et al. From blame to punishment: disrupting prefrontal cortex activity reveals norm enforcement mechanisms. Neuron 87, 1369–1380 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Treadway, M.T. et al. Corticolimbic gating of emotion-driven punishment. Nat. Neurosci. 17, 1270–1275 (2014).

    Article  CAS  PubMed  Google Scholar 

  30. Knoch, D., Pascual-Leone, A., Meyer, K., Treyer, V. & Fehr, E. Diminishing reciprocal fairness by disrupting the right prefrontal cortex. Science 314, 829–832 (2006).

    Article  CAS  PubMed  Google Scholar 

  31. Buckholtz, J.W. Social norms, self-control, and the value of antisocial behavior. Curr. Opin. Behav. Sci. 3, 122–129 (2015).

    Article  Google Scholar 

  32. Haber, S.N., Kim, K.-S., Mailly, P. & Calzavara, R. Reward-related cortical inputs define a large striatal region in primates that interface with associative cortical connections, providing a substrate for incentive-based learning. J. Neurosci. 26, 8368–8376 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Choi, E.Y., Yeo, B.T.T. & Buckner, R.L. The organization of the human striatum estimated by intrinsic functional connectivity. J. Neurophysiol. 108, 2242–2263 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  34. van den Bos, W., Rodriguez, C.A., Schweitzer, J.B. & McClure, S.M. Connectivity strength of dissociable striatal tracts predict individual differences in temporal discounting. J. Neurosci. 34, 10298–10310 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Daw, N.D. in Decision Making, Affect, and Learning: Attention and Performance XXIII (eds. Delgado, M.R., Phelps, E.A. & Robbins, T.W.) (Oxford University Press, 2011).

  36. Xie, W., Yu, B., Zhou, X., Sedikides, C. & Vohs, K.D. Money, moral transgressions, and blame. J. Consum. Psychol. 24, 299–306 (2014).

    Article  Google Scholar 

  37. Dolan, M. The neuropsychology of prefrontal function in antisocial personality disordered offenders with varying degrees of psychopathy. Psychol. Med. 42, 1715–1725 (2012).

    Article  CAS  PubMed  Google Scholar 

  38. Inbar, Y., Pizarro, D.A. & Cushman, F. Benefiting from misfortune: when harmless actions are judged to be morally blameworthy. Pers. Soc. Psychol. Bull. 38, 52–62 (2012).

    Article  PubMed  Google Scholar 

  39. Feng, C., Luo, Y.-J. & Krueger, F. Neural signatures of fairness-related normative decision making in the ultimatum game: a coordinate-based meta-analysis. Hum. Brain Mapp. 36, 591–602 (2015).

    Article  CAS  PubMed  Google Scholar 

  40. Moutoussis, M., Dolan, R.J. & Dayan, P. How people use social information to find out what to want in the paradigmatic case of inter-temporal preferences. PLOS Comput. Biol. 12, e1004965 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Garrett, N., Lazzaro, S.C., Ariely, D. & Sharot, T. The brain adapts to dishonesty. Nat. Neurosci. 19, 1727–1732 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Tai, L.-H., Lee, A.M., Benavidez, N., Bonci, A. & Wilbrecht, L. Transient stimulation of distinct subpopulations of striatal neurons mimics changes in action value. Nat. Neurosci. 15, 1281–1289 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Macpherson, T., Morita, M. & Hikida, T. Striatal direct and indirect pathways control decision-making behavior. Front. Psychol. 5, 1301 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Buckholtz, J.W. et al. Mesolimbic dopamine reward system hypersensitivity in individuals with psychopathic traits. Nat. Neurosci. 13, 419–421 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Couppis, M.H., Kennedy, C.H. & Stanwood, G.D. Differences in aggressive behavior and in the mesocorticolimbic DA system between A/J and BALB/cJ mice. Synapse 62, 715–724 (2008).

    Article  CAS  PubMed  Google Scholar 

  46. Jordan, M.R., Amir, D. & Bloom, P. Are empathy and concern psychologically distinct? Emotion 16, 1107–1116 (2016).

    Article  PubMed  Google Scholar 

  47. Ruff, C.C. & Fehr, E. The neurobiology of rewards and values in social decision making. Nat. Rev. Neurosci. 15, 549–562 (2014).

    Article  CAS  PubMed  Google Scholar 

  48. Hutton, C. et al. The impact of physiological noise correction on fMRI at 7 T. Neuroimage 57, 101–112 (2011).

    Article  CAS  PubMed  Google Scholar 

  49. Lindquist, M.A., Meng Loh, J., Atlas, L.Y. & Wager, T.D. Modeling the hemodynamic response function in fMRI: efficiency, bias and mis-modeling. Neuroimage 45 (Suppl. 1), S187–S198 (2009).

    Article  PubMed  Google Scholar 

  50. Pernet, C.R., Wilcox, R. & Rousselet, G.A. Robust correlation analyses: false positive and power validation using a new open source matlab toolbox. Front. Psychol. 3, 606 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Holmes, A. & Friston, K. Generalisability, random effects & population inference. Neuroimage 7, S754 (1998).

    Article  Google Scholar 

  52. Flandin, G. & Friston, K.J. Analysis of family-wise error rates in statistical parametric mapping using random field theory. Preprint at https://arxiv.org/abs/1606.08199 (2016).

  53. Bzdok, D. et al. Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy. Brain Struct. Funct. 217, 783–796 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Hare, T.A., Camerer, C.F. & Rangel, A. Self-control in decision-making involves modulation of the vmPFC valuation system. Science 324, 646–648 (2009).

    Article  CAS  PubMed  Google Scholar 

  55. Rudorf, S. & Hare, T.A. Interactions between dorsolateral and ventromedial prefrontal cortex underlie context-dependent stimulus valuation in goal-directed choice. J. Neurosci. 34, 15988–15996 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Hare, T.A., Malmaud, J. & Rangel, A. Focusing attention on the health aspects of foods changes value signals in vmPFC and improves dietary choice. J. Neurosci. 31, 11077–11087 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Hare, T.A., Hakimi, S. & Rangel, A. Activity in dlPFC and its effective connectivity to vmPFC are associated with temporal discounting. Front. Neurosci. 8, 50 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Maier, S.U., Makwana, A.B. & Hare, T.A. Acute stress impairs self-control in goal-directed choice by altering multiple functional connections within the brain's decision circuits. Neuron 87, 621–631 (2015).

    Article  CAS  PubMed  Google Scholar 

  59. Fisher, R.A. Statistical Methods for Research Workers (Genesis Publishing, 1925).

Download references

Acknowledgements

We thank E. Boorman, A. de Berker, L. Hunt, M. Klein-Flugge, C. Mathys, R. Rutledge, B. Seymour, P. Smittenaar, G. Story, I. Vlaev and J. Winston for feedback. M.J.C. was supported by a Sir Henry Wellcome Postdoctoral Fellowship (092217/Z/10/Z) and a Wellcome Trust Institutional Strategic Support Fund grant. J.Z.S. was supported by a Wellcome Trust Society and Ethics studentship (104980/Z/14/Z). Z.K.-N. was supported by a Joint Initiative on Computational Psychiatry and Ageing Research between the Max Planck Society and University College London. P.D. is funded by the Gatsby Charitable Foundation. R.J.D. holds a Wellcome Trust Senior Investigator Award (098362/Z/12/Z). The Max Planck UCL Centre is a joint initiative supported by UCL and the Max Planck Society. The Wellcome Trust Centre for Neuroimaging, where scanning was carried out, is supported by core funding from the Wellcome Trust (091593/Z/10/Z).

Author information

Authors and Affiliations

Authors

Contributions

M.J.C. conceived the study. M.J.C., J.Z.S., Z.K.-N., P.D. and R.J.D. designed the study. M.J.C. and J.Z.S. collected behavioral and fMRI data. M.J.C., J.Z.S., Z.K.-N. and P.D. analyzed the data. M.J.C. wrote the manuscript with edits from J.Z.S., Z.K.-N., P.D. and R.J.D.

Corresponding author

Correspondence to Molly J Crockett.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Blame judgment task.

Participants viewed others’ decisions and were asked to rate them on a scale from blameworthy to praiseworthy. Across trials we independently manipulated the amounts of profit and pain resulting from choices.

Supplementary Figure 2 Moral transgressions modulate relative chosen value signal in vmPFC.

(a) The model-derived subjective value of the chosen option, relative to the unchosen option, was correlated positively with BOLD responses in a widespread network including vmPFC (k=1157, p<0.0001), mid-posterior cingulate (PFWE <0.0001), precuneus (PFWE <0.0001), bilateral clusters encompassing amygdala, striatum and insula (PFWE <0.0001). Chosen relative to unchosen subjective value was correlated negatively with BOLD responses in mid-cingulate cortex and anterior insula (PFWE =0.0002). All results whole brain familywise error corrected at the cluster level after voxel-wise thresholding at p<0.001. Image displayed at p < 0.005, uncorrected to show extent of activation. (b) The value-sensitive region of vmPFC (circled in a) showed reduced sensitivity to the value of the harmful option in the other condition relative to the self condition (t(27)=2.51, p=0.019). *P < 0.05; n.s., nonsignificant. Error bars depict s.e.m.

Supplementary Figure 3 Neural representation of pain is uncorrelated with moral behavior.

(a) At choice onset, left TPJ activity positively correlated with the relative amount of pain a harmful choice could inflict on others, but not self (Δsother > Δsself, mean signal extracted from independently defined ROI in TPJ, t(27) = 2.61, p = 0.015). Image displayed at p<0.005, uncorrected to show extent of activation. (b) Parameter estimates for Δsother and Δsself extracted from ROI in TPJ. At choice onset, left TPJ activity positively correlated with Δsother (t(27) = 2.27, p = 0.031), but not Δsself (t(27) = -0.30, p = 0.77); difference Δsother > Δsself, t(27) = 2.61, p = 0.015). (c) Differential response to self vs. others’ pain in TPJ was uncorrelated with individual differences in moral preferences (r=-0.14, 95% CI=[-0.46 0.26]). (d) At choice onset, ACC activity positively correlated with the relative amount of pain a harmful choice could inflict on both self and others (Δsother Δsself, mean signal extracted from independently defined ROI in ACC, t(27) = 2.56, p = 0.016). Image displayed at p<0.005, uncorrected to show extent of activation. (e) Parameter estimates for Δsother and Δsself extracted from ROI in ACC. At choice onset, ACC activity positively correlated with Δsself (t(27) = 3.35, p = 0.002) but not Δsother (t(27) = 0.77, p = 0.45). ACC tended to respond more strongly to pain for self than other (t(27) = -1.91, p = 0.067). (f) Differential response to pain for self vs others in ACC was uncorrelated with individual differences in moral preferences (robust correlation, r=0.09, 95% CI=[-0.32 0.47]). Error bars depict s.e.m. *P < 0.05; **P < 0.01; n.s., nonsignificant; n.s.t., nonsignificant trend.

Supplementary Figure 4 Corticostriatal connectivity during moral decisions and value sensitivity in DS.

(a) For illustrative purposes we display parameter estimates for LPFC-DS connectivity during choices to help others, harm others, and help self, extracted from the DS cluster depicted in Fig. 4a. We note that this figure is purely illustrative, and we confine our inferences solely to those arising out of a comparison between conditions (which were significant in a whole brain analysis). (b) The extent to which DS activity was sensitive to relative chosen value predicted the degree of negative connectivity between DS and LPFC during moral choices (robust correlation, r =-0.51, 95% CI [-0.73 -0.14]). Error bars depict s.e.m.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–4, Supplementary Tables 1–9 and Supplementary Modelling Note. (PDF 1805 kb)

Supplementary Methods Checklist (PDF 912 kb)

Supplementary Software (ZIP 8 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Crockett, M., Siegel, J., Kurth-Nelson, Z. et al. Moral transgressions corrupt neural representations of value. Nat Neurosci 20, 879–885 (2017). https://doi.org/10.1038/nn.4557

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nn.4557

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing