Skip to main content

Thank you for visiting 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.

The brain adapts to dishonesty


Dishonesty is an integral part of our social world, influencing domains ranging from finance and politics to personal relationships. Anecdotally, digressions from a moral code are often described as a series of small breaches that grow over time. Here we provide empirical evidence for a gradual escalation of self-serving dishonesty and reveal a neural mechanism supporting it. Behaviorally, we show that the extent to which participants engage in self-serving dishonesty increases with repetition. Using functional MRI, we show that signal reduction in the amygdala is sensitive to the history of dishonest behavior, consistent with adaptation. Critically, the extent of reduced amygdala sensitivity to dishonesty on a present decision relative to the previous one predicts the magnitude of escalation of self-serving dishonesty on the next decision. The findings uncover a biological mechanism that supports a 'slippery slope': what begins as small acts of dishonesty can escalate into larger transgressions.

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

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type



Prices may be subject to local taxes which are calculated during checkout

Figure 1: Procedure and dishonesty escalation.
Figure 2: Replication and extension study.
Figure 3: Reduction in sensitivity to dishonesty over time.
Figure 4: Reduction in brain response to dishonesty predicts its escalation.


  1. Maremont, M. Anatomy of the Kurzweil fraud. Bus. Week 16 Sept. 1996.

  2. Kirchner, B. The Bernard Madoff Investment Scam (FT Press, 2010).

  3. McLean, B. & Elkind, P. The Smartest Guys in the Room: The Amazing Rise and Scandalous Fall of Enron (Penguin, 2013).

  4. Stapel, D. Ontsporing (Prometheus Amsterdam, 2012).

  5. Graham, C., Litan, R.E. & Sukhtankar, S. The Bigger They Are, The Harder They Fall: An Estimate of the Costs of the Crisis in Corporate Governance. (The Brookings Institution, 2002). Available at:

  6. Mauro, P. Corruption and growth. Q. J. Econ. 110, 681–712 (1995).

    Article  Google Scholar 

  7. Tanzi, V. & Davoodi, H. Corruption, Public Investment, and Growth (Springer, 1998).

  8. Heyneman, S.P., Anderson, K.H. & Nuraliyeva, N. The cost of corruption in higher education. Comp. Educ. Rev. 52, 1–25 (2008).

    Article  Google Scholar 

  9. Peterson, C. Deception in intimate relationships. Int. J. Psychol. 31, 279–288 (1996).

    Article  Google Scholar 

  10. DePaulo, B.M., Kashy, D.A., Kirkendol, S.E., Wyer, M.M. & Epstein, J.A. Lying in everyday life. J. Pers. Soc. Psychol. 70, 979–995 (1996).

    Article  CAS  PubMed  Google Scholar 

  11. Gamer, M., Rill, H.-G., Vossel, G. & Gödert, H.W. Psychophysiological and vocal measures in the detection of guilty knowledge. Int. J. Psychophysiol. 60, 76–87 (2006).

    Article  PubMed  Google Scholar 

  12. Abe, N., Suzuki, M., Mori, E., Itoh, M. & Fujii, T. Deceiving others: distinct neural responses of the prefrontal cortex and amygdala in simple fabrication and deception with social interactions. J. Cogn. Neurosci. 19, 287–295 (2007).

    Article  PubMed  Google Scholar 

  13. Schachter, S. & Latané, B. Crime, cognition, and the autonomic nervous system. In Nebr. Symp. Motiv. 12 (ed. Levine, D.) 221–275 (1964).

  14. Breiter, H.C. et al. Response and habituation of the human amygdala during visual processing of facial expression. Neuron 17, 875–887 (1996).

    Article  CAS  PubMed  Google Scholar 

  15. Ishai, A., Pessoa, L., Bikle, P.C. & Ungerleider, L.G. Repetition suppression of faces is modulated by emotion. Proc. Natl. Acad. Sci. USA 101, 9827–9832 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Denny, B.T. et al. Insula-amygdala functional connectivity is correlated with habituation to repeated negative images. Soc. Cogn. Affect. Neurosci. 9, 1660–1667 (2014).

    Article  PubMed  Google Scholar 

  17. Yarkoni, T., Poldrack, R.A., Nichols, T.E., Van Essen, D.C. & Wager, T.D. Large-scale automated synthesis of human functional neuroimaging data. Nat. Methods 8, 665–670 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Lane, R.D. et al. Neuroanatomical correlates of pleasant and unpleasant emotion. Neuropsychologia 35, 1437–1444 (1997).

    Article  CAS  PubMed  Google Scholar 

  19. Zald, D.H. & Pardo, J.V. Emotion, olfaction, and the human amygdala: amygdala activation during aversive olfactory stimulation. Proc. Natl. Acad. Sci. USA 94, 4119–4124 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Schneider, F. et al. Differential amygdala activation in schizophrenia during sadness. Schizophr. Res. 34, 133–142 (1998).

    Article  CAS  PubMed  Google Scholar 

  21. Ketter, T.A. et al. Anterior paralimbic mediation of procaine-induced emotional and psychosensory experiences. Arch. Gen. Psychiatry 53, 59–69 (1996).

    Article  CAS  PubMed  Google Scholar 

  22. Irwin, W. et al. Human amygdala activation detected with echo-planar functional magnetic resonance imaging. Neuroreport 7, 1765–1769 (1996).

    Article  CAS  PubMed  Google Scholar 

  23. Ledoux, J. The Emotional Brain: the Mysterious Underpinnings of Emotional Life (Simon & Schuster, 1998).

  24. Cain, D.M., Loewenstein, G. & Moore, D.A. The dirt on coming clean: perverse effects of disclosing conflicts of interest. J. Legal Stud. 34, 1–25 (2005).

    Article  Google Scholar 

  25. Costa, V.D., Lang, P.J., Sabatinelli, D., Versace, F. & Bradley, M.M. Emotional imagery: assessing pleasure and arousal in the brain's reward circuitry. Hum. Brain Mapp. 31, 1446–1457 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Knutson, B., Adams, C.M., Fong, G.W. & Hommer, D. Anticipation of increasing monetary reward selectively recruits nucleus accumbens. J. Neurosci. 21, RC159 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. MacDonald, A.W. III, Cohen, J.D., Stenger, V.A. & Carter, C.S. Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. Science 288, 1835–1838 (2000).

    Article  CAS  PubMed  Google Scholar 

  28. Miller, E.K. & Cohen, J.D. An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci. 24, 167–202 (2001).

    Article  CAS  PubMed  Google Scholar 

  29. 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 

  30. Zhu, L. et al. Damage to dorsolateral prefrontal cortex affects tradeoffs between honesty and self-interest. Nat. Neurosci. 17, 1319–1321 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Langleben, D.D. et al. Telling truth from lie in individual subjects with fast event-related fMRI. Hum. Brain Mapp. 26, 262–272 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Mohamed, F.B. et al. Brain mapping of deception and truth telling about an ecologically valid situation: functional MR imaging and polygraph investigation–initial experience. Radiology 238, 679–688 (2006).

    Article  PubMed  Google Scholar 

  33. Chang, L.J., Gianaros, P.J., Manuck, S.B., Krishnan, A. & Wager, T.D. A sensitive and specific neural signature for picture-induced negative affect. PLoS Biol. 13, e1002180 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Winnett, R. & Rayner, G. No Expenses Spared (Bantam Press, 2009).

  35. Welsh, D.T., Ordóñez, L.D., Snyder, D.G. & Christian, M.S. The slippery slope: how small ethical transgressions pave the way for larger future transgressions. J. Appl. Psychol. 100, 114–127 (2015).

    Article  PubMed  Google Scholar 

  36. Schrand, C.M. & Zechman, S.L.C. Executive overconfidence and the slippery slope to financial misreporting. J. Account. Econ. 53, 311–329 (2012).

    Article  Google Scholar 

  37. LeDoux, J.E. Emotion circuits in the brain. Annu. Rev. Neurosci. 23, 155–184 (2000).

    Article  CAS  PubMed  Google Scholar 

  38. Phelps, E.A. Emotion and cognition: insights from studies of the human amygdala. Annu. Rev. Psychol. 57, 27–53 (2006).

    Article  PubMed  Google Scholar 

  39. Poldrack, R.A. Can cognitive processes be inferred from neuroimaging data? Trends Cogn. Sci. 10, 59–63 (2006).

    Article  PubMed  Google Scholar 

  40. Shenhav, A. & Greene, J.D. Integrative moral judgment: dissociating the roles of the amygdala and ventromedial prefrontal cortex. J. Neurosci. 34, 4741–4749 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Wu, D., Loke, I.C., Xu, F. & Lee, K. Neural correlates of evaluations of lying and truth-telling in different social contexts. Brain Res. 1389, 115–124 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Mazar, N., Amir, O. & Ariely, D. The dishonesty of honest people: a theory of self-concept maintenance. J. Mark. Res. 45, 633–644 (2008).

    Article  Google Scholar 

  43. Effron, D.A., Bryan, C.J. & Murnighan, J.K. Cheating at the end to avoid regret. J. Pers. Soc. Psychol. 109, 395–414 (2015).

    Article  PubMed  Google Scholar 

  44. Eickhoff, S.B. et al. A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. Neuroimage 25, 1325–1335 (2005).

    Article  PubMed  Google Scholar 

  45. Eickhoff, S.B., Heim, S., Zilles, K. & Amunts, K. Testing anatomically specified hypotheses in functional imaging using cytoarchitectonic maps. Neuroimage 32, 570–582 (2006).

    Article  PubMed  Google Scholar 

  46. Charpentier, C.J., Moutsiana, C., Garrett, N. & Sharot, T. The brain's temporal dynamics from a collective decision to individual action. J. Neurosci. 34, 5816–5823 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Edelson, M.G., Dudai, Y., Dolan, R.J. & Sharot, T. Brain substrates of recovery from misleading influence. J. Neurosci. 34, 7744–7753 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Drueke, B. et al. Neural correlates of positive and negative performance feedback in younger and older adults. Behav. Brain Funct. 11, 17 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Maldjian, J.A., Laurienti, P.J., Kraft, R.A. & Burdette, J.H. An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets. Neuroimage 19, 1233–1239 (2003).

    Article  PubMed  Google Scholar 

  50. Slavich, G.M., Way, B.M., Eisenberger, N.I. & Taylor, S.E. Neural sensitivity to social rejection is associated with inflammatory responses to social stress. Proc. Natl. Acad. Sci. USA 107, 14817–14822 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references


We thank D. Prelec, B. Baharami, U. Hertz, J. Navajas and D. Bang for helpful discussions; T. Yarkoni, C. Frith and W. Penny for advice; R. Rutledge, C. Summerfield, M. Cikara, M. Edelson, R. Köster, A. Kappes, C. Charpentier, S. Suarez, L. Coutrot, L. Wittkuhn and P. Czech for comments on previous versions of this manuscript; and T. Srirangarajan, R. Anjum, S. Hadden, G. Montinola and M. Wilner for assistance with data collection and scanning; T.S. is supported by a Wellcome Trust Career Development Fellowship 093807/Z/10/Z and N.G. by a UCL Impact Award; the research was also supported by funding from the Center for Advanced Hindsight.

Author information

Authors and Affiliations



T.S. conceived the study. N.G., S.C.L., D.A. and T.S. designed the study. N.G. collected behavioral and fMRI data. N.G. and T.S. analyzed the data. N.G. and T.S. wrote the manuscript with edits from S.C.L.

Corresponding authors

Correspondence to Neil Garrett or Tali Sharot.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Mean dishonesty and starting dishonesty

(a) Mean dishonesty over the course of the block (Self-Serving-Other-Harming: t54 = 5.49, p<0.001; Self-Serving-Other-Serving: t54 = 6.16, p<0.001; Self-Harming-Other-Serving: t54 = -0.39, p=0.70 - one sample ttests vs 0; comparisons between conditions: Self-Serving-Other-Harming vs Self-Harming-Other-Serving: F1,53 = 26.44, p<0.001; Self-Serving-Other-Serving vs Self-Harming-Other-Serving: F1,53 = 39.67 p<0.0001; Self-Serving-Other-Serving vs Self-Serving-Other-Harming: F1,53 = 7.72, p=0.008 - statistics reported for separate 2 way ANOVAs with condition as a 2 level repeated factor controlling for study). (b) Starting dishonesty (Self-Serving-Other-Harming: t54 = 4.48, p<0.001; Self-Serving-Other-Serving: t54 = 5.56, p<0.001; Self-Harming-Other-Serving: t54 = 1.69, p=0.097, one sample ttests vs 0; Self-Serving-Other-Harming vs Self-Harming-Other-Serving condition: F1,53 = 7.74, p=0.007; Self-Serving-Other-Serving vs Self-Harming-Other-Serving condition: F1,53 = 21.99, p<0.001; F1,53 = 8.84, p=0.004, 2 way repeated measure ANOVAs controlling for study). N=55.

Error bars represent standard error of the mean.

*p<0.05, n.s. = non-significant

Supplementary Figure 2 Voxels restricted to bilateral amygdala

fMRI analysis was repeated on voxels in our ROI that were restricted to the anatomically defined amygdala. This analysis generated similar results as those portrayed in Figures 3, 4. Specifically, (a) time-weighted dishonesty regressor positively correlated with BOLD response when dishonesty was Self-Serving-Other-Harming (t24 = 2.68, p=0.01, one sample ttest vs 0) but not when it was Self-Harming-Other-Serving (t24 = -0.9, p=0.38, one sample ttest vs 0) with the former parameter betas significantly greater than the latter (t24 = 2.60, p=0.02, paired sample ttest). (b) Reduction in BOLD response to one unit dishonesty on a current trial relative to the last predicted dishonesty escalation on next trial relative to current trial, when dishonesty was Self-Serving-Other-Harming (t24 = 2.30, p=0.03, one sample ttest vs 0) but not when Self-Harming-Other-Serving (trend in opposite direction t24 = -1.77, p=0.09, one sample ttest vs 0) with the former betas significantly larger than the latter (t24 = 3.05, p=0.01, paired sample ttest). N=25.

Error bars represent standard error of the mean.

*p<0.05, n.s. = non-significant

Supplementary Figure 3 Awareness of dishonesty

Fifteen participants, who completed the task outside of the scanner in testing cubicles in Experiment 1, were also asked immediately after the Self-Serving-Other-Harming block of trials to estimate the magnitude by which they gave advice over and above what they actually thought was in the jar on the last trial, as well as on average throughout that block (order of these two questions was counterbalanced). Participants did not know in advance that they would be asked to do this. Comparing participants’ self-reports to their actual dishonesty revealed no significant differences on the last trial (t14 = 0.04, p>0.95, one sample ttest against a test value of 0) and on average (t14 = 1.29, p=0.22, one sample ttest against a test value of 0).

n.s. = non significant

Supplementary Figure 4 Baseline accuracy

(a) Mean absolute error in the baseline condition (t54 = 19.06, p<0.001, n=55, one sample ttest vs 0). (b) Parameters show that errors were not changing with time in the baseline condition (regressing error rate over the 60 trials on trial number for each participant revealed no change over time: t54 = 0.67, p=0.51, n=55, one sample ttest vs 0). As participants did not receive any feedback it is not surprising that they did not show significant improvement over the course of the block.

Error bars represent standard error of the mean.


Supplementary Figure 5 Reaction time

RTs were slower in the Self-Harming-Other-Serving condition than the Self-Serving-Other-Serving condition (t54 = -2.19, p=0.03, n=55, paired sample ttest). Note, there was no correlation between mean RT and escalation of dishonesty in any of the conditions (all P > 0.3).

Error bars represent standard error of the mean.


Supplementary information

Supplementary Text and figures

Supplementary Figures 1–5 and Supplementary Tables 1–4 (PDF 712 kb)

Supplementary Methods Checklist (PDF 608 kb)

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Garrett, N., Lazzaro, S., Ariely, D. et al. The brain adapts to dishonesty. Nat Neurosci 19, 1727–1732 (2016).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


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