Brain response patterns to economic inequity predict present and future depression indices

  • Nature Human Behaviourvolume 1pages748756 (2017)
  • doi:10.1038/s41562-017-0207-1
  • Download Citation
Published online:


Widening economic inequity has been suggested to associate with depression. However, little is known about the underlying neural mechanisms of this link. Here, we demonstrate that functional magnetic resonance imaging activity patterns in the amygdala and hippocampus induced by the inequity between the self and other rewards during an economic game can predict participants’ present and future (measured one year later) depression indices. Such predictions were not possible using participant’s behavioural and socio-economic status measures. These findings suggest that sensitivity to economic inequity has a critical effect on human mood states, and the amygdala and hippocampus play a key role in individual differences in the effect.

Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


  1. 1.

    Piketty, T. Capital in the Twenty-first Century (Belknap Press, Cambridge, MA, 2014).

  2. 2.

    Kawachi, I. & Kennedy, B. P. The Health of Nation: Why Inequity is Harmful to Your Health (The New Press, New York, NY, 2002).

  3. 3.

    Wilkinson, R. G. & Pickett, K. E. Income inequality and population health: a review and explanation of the evidence. Soc. Sci. Med. 62, 1768–1784 (2006).

  4. 4.

    Marmot, M. G. et al. Health inequalities among British civil servants: the Whitehall II study. The Lancet 337, 1387–1393 (1991).

  5. 5.

    Hamad, R., Fernald, L. C., Karlan, D. S. & Zinman, J. Social and economic correlates of depressive symptoms and perceived stress in South African adults. J. Epidemiol. Community Health 62, 538–544 (2008).

  6. 6.

    Stansfeld, S. A., Head, J., Fuhrer, R., Wardle, J. & Cattell, V. Social inequalities in depressive symptoms and physical functioning in the Whitehall II study: exploring a common cause explanation. J. Epidemiol. Community Health 57, 361–367 (2003).

  7. 7.

    Turner, R. J., Lloyd, D. A. & Roszell, P. Personal resources and the social distribution of depression. Am. J. Community Psychol. 27, 643–672 (1999).

  8. 8.

    Jang, K. L. The Behavioral Genetics of Psychopathology: A Clinical Guide (Lawrence Erlbaum Association, Mahwah, NJ, 2008).

  9. 9.

    Messick, D. M. & McClintock, C. G. Motivational bases of choice in experimental games. J. Exp. Soc. Psychol. 4, 1–25 (1968).

  10. 10.

    Van Lange, P. A. M. The pursuit of joint outcomes and equality in outcomes: an integrative model of social value orientation. J. Pers. Soc. Psychol. 77, 337–349 (1999).

  11. 11.

    Gospic, K. et al. Limbic justice—amygdala involvement in immediate rejection in the Ultimatum Game. PLoS Biol. 9, e1001054 (2011).

  12. 12.

    Haruno, M. & Frith, C. D. Activity in the amygdala elicited by unfair divisions predicts social value orientation. Nat. Neurosci. 13, 160–161 (2010).

  13. 13.

    Haruno, M., Kimura, M. & Frith, C. D. Activity in the nucleus accumbens and amygdala underlies individual differences in prosocial and individualistic economic choices. J. Cog. Neurosci. 26, 1861–1870 (2014).

  14. 14.

    Groenewold, N. A., Opmeer, E. M., de Jonge, P., Aleman, A. & Costafreda, S. G. Emotional valence modulates brain functional abnormalities in depression: evidence from a meta-analysis of fMRI studies. Neurosci. Biobehav. Rev. 37, 152–163 (2013).

  15. 15.

    Matthews, S. C., Strigo, I. A., Simmons, A. N., Yang, T. T. & Paulus, M. P. Decreased functional coupling of the amygdala and supragenual cingulate is related to increased depression in unmedicated individuals with current major depressive disorder. J. Affect. Disord. 111, 13–20 (2008).

  16. 16.

    Bremner, J. D. et al. Hippocampal volume reduction in major depression. Am. J. Psychiatry 157, 115–118 (2000).

  17. 17.

    Lorenzetti, V., Allen, N. B., Fornito, A. & Yücel, M. Structural brain abnormalities in major depressive disorder: a selective review of recent MRI studies. J. Affect. Disord. 117, 1–17 (2009).

  18. 18.

    Sheline, Y. I., Wang, P. W., Gado, M. H., Csernansky, J. G. & Vannier, M. W. Hippocampal atrophy in recurrent major depression. Proc. Natl Acad. Sci. USA 93, 3908–3913 (1996).

  19. 19.

    Nestler, E. J., Hyman, S. E. & Malenka, R. J. Molecular Neuro-pharmacology. A Foundation for Clinical Neuroscience 2nd edn (McGraw-Hill, New York, NY, 2009).

  20. 20.

    Akiskal, H. S., Hirschfeld, R. M. & Yerevanian, B. I. The relationship of personality to affective disorders. Arc. Gen. Psychiatry 40, 801–810 (1983).

  21. 21.

    Von Zerssen, D., Tauscher, R. & Possl, J. The relationship of premorbid personality to subtypes of an affective illness. A replication study by means of an operationalized procedure for the diagnosis of personality structures. J. Affect. Disord. 32, 61–72 (1994).

  22. 22.

    Güth, W., Schmittberger, R. & Schwarze, B. An experimental analysis of ultimatum bargaining. J. Econ. Behav. Organ. 3, 367–388 (1982).

  23. 23.

    Sanfey, A. G., Rilling, J. K., Aronson, J. A., Nystrom, L. E. & Cohen, J. D. The neural basis of economic decision-making in the ultimatum game. Science 300, 1755–1758 (2003).

  24. 24.

    Beck, A. T., Steer, R. A., Ball, R. & Ranieri, W. Comparison of Beck Depression Inventories -IA and -II in psychiatric outpatients. J. Pers. Assess. 67, 588–597 (1996).

  25. 25.

    Tricomi, E., Rangel, A., Camerer, C. & O’Doherty, J. Neural evidence for inequality averse social preferences. Nature 463, 1089–1091 (2011).

  26. 26.

    Schmaal, L. et al. Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group. Mol. Psychiatry 21, 806–812 (2016).

  27. 27.

    Michl, P. et al. Neurobiological underpinnings of shame and guilt: a pilot fMRI study. Soc. Cogn. Affect. Neurosci. 9, 150–157 (2014).

  28. 28.

    Doerig, N. et al. Neural representation and clinically relevant moderators of individualised self-criticism in healthy subjects. Soc. Cogn. Affect. Neurosci. 9, 1333–1340 (2014).

  29. 29.

    Eldar, E. & Niv, Y. Interaction between emotional state and learning underlies mood instability. Nat. Commun. 6, 6149 (2015).

  30. 30.

    Eldar, E., Rutledge, R. B., Dolan, R. J. & Niv, Y. Mood as representation of momentum. Trends Cogn. Sci. 20, 15–24 (2016).

  31. 31.

    Headey, B. & Veenhoven, R. in How Harmful is Hapiness? Consequences of Enjoying Life or Not (ed. Veenhoven, R.) 106–127 (Universitaire Pers, Rotterdam, 1989).

  32. 32.

    Drysdale, A. T. et al. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat. Med. 23, 28–38 (2017).

  33. 33.

    Ogawa, T. & Oda, M. Construction and Evaluation of the Facial Expression Database ATR Technical Report TR-H-244 (1998).

  34. 34.

    Bishop, C. M. Pattern Recognition and Machine Learning (Springer, New York, NY, 2006).

  35. 35.

    Shawe-Taylor, J. & Cristianini, N. Kernel Methods for Pattern Analysis (University Press, Cambridge, 2004).

  36. 36.

    Tipping, M. E. Sparse bayesian learning and the relevance vector machine. J. Mach. Learn. Res. 1, 211–244 (2001).

  37. 37.

    Vapnik, V., Golowich, S. E. & Smola, A. Support vector method for function approximation, regression estimation, and signal processing. In Proc. 9th International Conference on Neural Information Processing Systems 281–287 (MIT Press, Cambridge, MA, 1996).

Download references


This work was supported by Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency (JST), the Center of Innovation at Osaka University and Grant-in-Aid for Scientific Research (KAKENNHI) (17H06314 and 26242087). We are grateful to S. Tada and T. Haji for technical assistance and P. Karagiannis for editing an early version of the manuscript. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information


  1. Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka 565-0871, Japan

    • Toshiko Tanaka
    •  & Masahiko Haruno
  2. Brain Science Institute, Tamagawa University, Tokyo 194-8610, Japan

    • Toshiko Tanaka
    •  & Masahiko Haruno
  3. NHK (Japan Broadcasting Corporation), Tokyo 150-8001, Japan

    • Takao Yamamoto


  1. Search for Toshiko Tanaka in:

  2. Search for Takao Yamamoto in:

  3. Search for Masahiko Haruno in:


M.H. and T.Y. designed the study. T.T. conducted the experiment. T.T. and M.H. analysed the data. T.T. and M.H. wrote the paper.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Masahiko Haruno.

Electronic supplementary material

  1. Supplementary Information

    Supplementary Figures 1–9, Supplementary Tables 1–5, Supplementary Methods

  2. Life Sciences Reporting Summary and Reporting Summary for MRI studies

    Life Science Reporting Summary and Reporting Summary for MRI