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.

  • Article
  • Published:

Explicit representation of confidence informs future value-based decisions

Nature Human Behaviour volume 1, Article number: 0002 (2017) Cite this article

Subjects

Abstract

Humans can reflect on decisions and report variable levels of confidence. But why maintain an explicit representation of confidence for choices that have already been made and therefore cannot be undone? Here we show that an explicit representation of confidence is harnessed for subsequent changes of mind. Specifically, when confidence is low, participants are more likely to change their minds when the same choice is presented again, an effect that is most pronounced in participants with greater fidelity in their confidence reports. Furthermore, we show that choices reported with high confidence follow a more consistent pattern (fewer transitivity violations). Finally, by tracking participants’ eye movements, we demonstrate that lower-level gaze dynamics can track uncertainty but do not directly impact changes of mind. These results suggest that an explicit and accurate representation of confidence has a positive impact on the quality of future value-based decisions.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Figure 1: Relation between confidence and choice.
Figure 2: Factors that contribute to confidence
Figure 3: Confidence predicts change of mind
Figure 4: Link between confidence and transitivity.

Similar content being viewed by others

References

  1. De Martino, B., Fleming, S. M., Garrett, N. & Dolan, R. J. Confidence in value-based choice. Nat. Neurosci. 16, 105–110 (2013).

    Article  CAS  PubMed  Google Scholar 

  2. Kepecs, A., Uchida, N., Zariwala, H. A. & Mainen, Z. F. Neural correlates, computation and behavioural impact of decision confidence. Nature 455, 227–231 (2008).

    Article  CAS  PubMed  Google Scholar 

  3. Kiani, R., Corthell, L. & Shadlen, M. N. Choice certainty is informed by both evidence and decision time. Neuron 84, 1329–1342 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Van den Berg, R. et al. A common mechanism underlies changes of mind about decisions and confidence. eLife 5, e12192 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Lebreton, M., Abitbol, R., Daunizeau, J. & Pessiglione, M. Automatic integration of confidence in the brain valuation signal. Nat. Neurosci. 18, 1159–1167 (2015).

    Article  CAS  PubMed  Google Scholar 

  6. Barron, H. C., Garvert, M. M. & Behrens, T. E. Reassessing VMPFC: full of confidence? Nat. Neurosci. 18, 1064–1066 (2015).

    Article  CAS  PubMed  Google Scholar 

  7. Meyniel, F., Sigman, M. & Mainen, Z. F. Confidence as Bayesian probability: from neural origins to behavior. Neuron 88, 78–92 (2015).

    Article  CAS  PubMed  Google Scholar 

  8. Pouget, A., Drugowitsch, J. & Kepecs, A. Confidence and certainty: distinct probabilistic quantities for different goals. Nat. Neurosci. 19, 366–374 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Fleming, S. M., Huijgen, J. & Dolan, R. J. Prefrontal contributions to metacognition in perceptual decision making. J. Neurosci. 32, 6117–6125 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Fleming, S. M., Weil, R. S., Nagy, Z., Dolan, R. J. & Rees, G. Relating introspective accuracy to individual differences in brain structure. Science 329, 1541–1543 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Rounis, E., Maniscalco, B., Rothwell, J. C., Passingham, R. E. & Lau, H. Theta-burst transcranial magnetic stimulation to the prefrontal cortex impairs metacognitive visual awareness. Cogn. Neurosci. 1, 165–175 (2010).

    Article  PubMed  Google Scholar 

  12. Bahrami, B. What failure in collective decision-making tells us about metacognition. Phil. Trans. R. Soc. B 367, 1350–1365 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Bang, D. et al. Does interaction matter? Testing whether a confidence heuristic can replace interaction in collective decision-making. Conscious. Cogn. 26, 13–23 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Lau, H. & Rosenthal, D. Empirical support for higher-order theories of conscious awareness. Trends. Cogn. Sci. 15, 365–373 (2011).

    Article  PubMed  Google Scholar 

  15. Resulaj, A., Kiani, R., Wolpert, D. M. & Shadlen, M. N. Changes of mind in decision-making. Nature 461, 263–266 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Yeung, N. & Summerfield, C. Metacognition in human decision-making: confidence and error monitoring. Phil. Trans. R. Soc. B. 367, 1310–1321 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Becker, G. M., DeGroot, M. H. & Marschak, J. Measuring utility by a single-response sequential method. Behav. Sci. 9, 226–232 (1964).

    Article  CAS  PubMed  Google Scholar 

  18. Boorman, E. D., Behrens, T. E. J., Woolrich, M. W. & Rushworth, M. F. S. How green is the grass on the other side? Frontopolar cortex and the evidence in favor of alternative courses of action. Neuron 62, 733–743 (2009).

    Article  CAS  PubMed  Google Scholar 

  19. FitzGerald, T. H. B., Seymour, B. & Dolan, R. J. The role of human orbitofrontal cortex in value comparison for incommensurable objects. J. Neurosci. 29, 8388–8395 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Lebreton, M., Jorge, S., Michel, V., Thirion, B. & Pessiglione, M. An automatic valuation system in the human brain: evidence from functional neuroimaging. Neuron 64, 431–439 (2009).

    Article  CAS  PubMed  Google Scholar 

  21. Levy, I., Lazzaro, S. C., Rutledge, R. B. & Glimcher, P. W. Choice from non-choice: predicting consumer preferences from blood oxygenation level-dependent signals obtained during passive viewing. J. Neurosci. 31, 118–125 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Plassmann, H., O'Doherty, J. P. & Rangel, A. Appetitive and aversive goal values are encoded in the medial orbitofrontal cortex at the time of decision making. J. Neurosci. 30, 10799–10808 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Krajbich, I. & Rangel, A. Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions. Proc. Natl Acad. Sci. USA 108, 13852–13857 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Carandini, M. & Heeger, D. J. Normalization as a canonical neural computation. Nat. Rev. Neurosci. 13, 51–62 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Louie, K. & Khaw, M. W. Normalization is a general neural mechanism for context-dependent decision making. Proc. Natl Acad. Sci. USA 110, 6139–6144 (2013).

    Article  MathSciNet  CAS  PubMed  PubMed Central  Google Scholar 

  26. Soltani, A., De Martino, B. & Camerer, C. A range-normalization model of context-dependent choice: a new model and evidence. PLoS Comput. Biol. 8, e1002607 (2012).

    Article  MathSciNet  CAS  PubMed  PubMed Central  Google Scholar 

  27. Krajbich, I., Armel, C. & Rangel, A. Visual fixations and the computation and comparison of value in simple choice. Nat. Neurosci. 13, 1292–1298 (2010).

    Article  CAS  PubMed  Google Scholar 

  28. Kiani, R. & Shadlen, M. N. Representation of confidence associated with a decision by neurons in the parietal cortex. Science 324, 759–764 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Bronfman, Z. Z. Decisions reduce sensitivity to subsequent information. Proc. Biol. Sci. 282, 20150228 (2015).

    PubMed  PubMed Central  Google Scholar 

  30. Moran, R., Teodorescu, A. R. & Usher, M. Post choice information integration as a causal determinant of confidence: Novel data and a computational account. Cogn. Psychol. 78, 99–147 (2015).

    Article  PubMed  Google Scholar 

  31. de Gardelle, V. & Mamassian, P. Does confidence use a common currency across two visual tasks? Psychol. Sci. 25, 1286–1288 (2014).

    Article  PubMed  Google Scholar 

  32. Fleming, S. M. & Lau, H. C. How to measure metacognition. Front. Hum. Neurosci. 8, 1–9 (2014).

    Article  Google Scholar 

  33. Neumann, Von, J., Morgenstern, O., Rubinstein, A. & Kuhn, H. W. Theory of Games and Economic Behavior (Princeton Univ. Press, 2007).

  34. Camerer, C. F. & Ho, T.-H. Violations of the betweenness axiom and nonlinearity in probability. J. Risk Uncertain. 8, 167–196 (1994).

    Article  Google Scholar 

  35. Loomes, G., Starmer, C. & Sugden, R. Observing violations of transitivity by experimental methods. Econometrica 59, 425–439 (1991).

    Article  MathSciNet  Google Scholar 

  36. Pedings, K. E., Langville, A. N. & Yamamoto, Y. A minimum violations ranking method. Optim. Eng. 13, 349–370 (2011).

    Article  MathSciNet  Google Scholar 

  37. Afriat, S. N. Efficiency estimation of production functions. Int. Econ. Rev. 13, 568–598 (1972).

    Article  MathSciNet  Google Scholar 

  38. Varian, H. R. Goodness-of-fit in optimizing models. J. Econ. 46, 125–140 (1990).

    Article  Google Scholar 

  39. Kepecs, A. & Mainen, Z. F. A computational framework for the study of confidence in humans and animals. Phil. Trans. R. Soc. B 367, 1322–1337 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Meyniel, F., Schlunegger, D. & Dehaene, S. The sense of confidence during probabilistic learning: a normative account. PLoS Comput. Biol. 11, e1004305 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Daw, N. D., O'Doherty, J. P., Dayan, P., Seymour, B. & Dolan, R. J. Cortical substrates for exploratory decisions in humans. Nature 441, 876–879 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Badre, D., Doll, B. B., Long, N. M. & Frank, M. J. Rostrolateral prefrontal cortex and individual differences in uncertainty-driven exploration. Neuron 73, 595–607 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Koechlin, E. & Hyafil, A. Anterior prefrontal function and the limits of human decision-making. Science 318, 594–598 (2007).

    Article  CAS  PubMed  Google Scholar 

  44. Rushworth, M. F. S. & Behrens, T. E. J. Choice, uncertainty and value in prefrontal and cingulate cortex. Nat. Neurosci. 11, 389–397 (2008).

    Article  CAS  PubMed  Google Scholar 

  45. Yoshida, W. & Ishii, S. Resolution of uncertainty in prefrontal cortex. Neuron 50, 781–789 (2006).

    Article  CAS  PubMed  Google Scholar 

  46. Donoso, M., Collins, A. & Koechlin, E. Foundations of human reasoning in the prefrontal cortex. Science 344, 1481–1486 (2014).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Payzan-LeNestour, E., Dunne, S., Bossaerts, P. & O'Doherty, J. P. The neural representation of unexpected uncertainty during value-based decision making. Neuron 79, 191–201 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Hájek, A. The Oxford Handbook of Rational and Social Choice (Anand, P., Pattanaik, P. K. & Puppe, C. eds) 173–195 (Oxford Univ. Press, 2008).

  50. Boldt, A. & Yeung, N. Shared neural markers of decision confidence and error detection. J. Neurosci. 35, 3478–3484 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Koizumi, A., Maniscalco, B. & Lau, H. Does perceptual confidence facilitate cognitive control? Atten. Percept. Psychophys. 77, 1295–1306 (2015).

    Article  PubMed  Google Scholar 

  52. Summerfield, C. Building bridges between perceptual and economic decision-making: neural and computational mechanisms. Front. Neurosci. 6, 70 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Brainard, D. H. The psychophysics toolbox. Spat. Vis. 10, 433–436 (1997).

    Article  CAS  PubMed  Google Scholar 

  54. Cornelissen, F. W., Peters, E. M. & Palmer, J. The Eyelink Toolbox: eye tracking with MATLAB and the Psychophysics Toolbox. Behav. Res. Methods Instrum. Comput. 34, 613–617 (2002).

    Article  PubMed  Google Scholar 

  55. Rapp, K. et al. Fasting blood glucose and cancer risk in a cohort of more than 140,000 adults in Austria. Diabetologia 49, 945–952 (2006).

    Article  CAS  PubMed  Google Scholar 

  56. Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting Linear Mixed-Effects Models Using lme4. J. Stat. Softw, 67, 1–48 (2015).

    Article  Google Scholar 

  57. Halekoh, U. & Højsgaard, S. A Kenward-Roger approximation and parametric bootstrap methods for tests in linear mixed models–the R package pbkrtest. J. Stat. Softw. 59, 1–30 (2014).

    Article  Google Scholar 

  58. Gelman, A. & Hill, J. Data Analysis using Regression and Multilevel/hierarchical Model. (Cambridge Univ. Press, 2006).

  59. Bolker, B. How trustworthy are the confidence intervals for lmer objects through the effects package? Stack Exchange (accessed 10 December 2015); http://stats.stackexchange.com/questions/117641/how-trustworthy-are-the-confidence-intervals-for-lmer-objects-through-effects-pa

  60. Gelman, A. & Pardoe, I. Bayesian measures of explained variance and pooling in multilevel (hierarchical) models. Technometrics 48, 241–251 (2006).

    Article  MathSciNet  Google Scholar 

  61. Folke, T. Explicit representations of confidence informs future value-based decisions. figsharehttps://dx.doi.org/10.6084/m9.figshare.3756144.v2 (2016).

Download references

Acknowledgements

This work was supported by the Wellcome Trust and Royal Society (Henry Dale Fellowship no. 102612/Z/13/Z to B.D.M.) and the Economics and Social Research Council (PhD scholarship for T.F.). The funders had no role in the study design, the data collection and analysis, the decision to publish, or the preparation of the manuscript. We would like to thank Y. Yamamoto for sharing the methods he developed to rank choice in experiment 1 and C. Street and S. Bobadilla Suarez for help in collecting the data and pre-processing the eye-tracking raw data used in experiment 1. We also thank C. Ruff for suggesting an appropriate name for the GSF variable.

Author information

Authors and Affiliations

  1. Department of Psychology, University of Cambridge, Downing Street, Cambridge, CB2 3EB, UK

    Tomas Folke

  2. Department of Food and Resource Economics, University of Copenhagen, Rolighedsvej 25, DK-1958 Frederiksberg C, Copenhagen, Denmark

    Catrine Jacobsen

  3. University College London, Wellcome Trust Centre for Neuroimaging, 12 Queen Square, London, WC1N 3BG, UK

    Stephen M. Fleming

  4. Institute of Cognitive Neuroscience, 17–19 Queen Square, London, WC1N 3AR, UK

    Benedetto De Martino

Authors
  1. Tomas Folke
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Catrine Jacobsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Stephen M. Fleming
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Benedetto De Martino
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

B.D.M., C.J. and S.M.F. designed the first experiment reported in this paper. The data for the first experiment were collected by C.J. The second experiment was designed by T.F. and B.D.M. The data for the second experiment were collected by T.F., and the data from both experiments were analysed by T.F. The article was written by B.D.M. and T.F. All authors revised the manuscript.

Corresponding author

Correspondence to Benedetto De Martino.

Ethics declarations

Competing interests

The authors declare no competing interests.

Supplementary information

Supplementary information

Supplementary Figures 1–7, Supplementary Tables 1–16, Supplementary Methods and Supplementary Results (PDF 885 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Folke, T., Jacobsen, C., Fleming, S. et al. Explicit representation of confidence informs future value-based decisions. Nat Hum Behav 1, 0002 (2017). https://doi.org/10.1038/s41562-016-0002

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41562-016-0002

This article is cited by

Search

Advanced 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