Confidence reports in decision-making with multiple alternatives violate the Bayesian confidence hypothesis.

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  • Author(s): Li HH;Li HH; Ma WJ; Ma WJ; Ma WJ
  • Source:
    Nature communications [Nat Commun] 2020 Apr 24; Vol. 11 (1), pp. 2004. Date of Electronic Publication: 2020 Apr 24.
  • Publication Type:
    Journal Article
  • Language:
    English
  • Additional Information
    • Source:
      Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE
    • Publication Information:
      Original Publication: [London] : Nature Pub. Group
    • Subject Terms:
    • Abstract:
      Decision confidence reflects our ability to evaluate the quality of decisions and guides subsequent behavior. Experiments on confidence reports have almost exclusively focused on two-alternative decision-making. In this realm, the leading theory is that confidence reflects the probability that a decision is correct (the posterior probability of the chosen option). There is, however, another possibility, namely that people are less confident if the best two options are closer to each other in posterior probability, regardless of how probable they are in absolute terms. This possibility has not previously been considered because in two-alternative decisions, it reduces to the leading theory. Here, we test this alternative theory in a three-alternative visual categorization task. We found that confidence reports are best explained by the difference between the posterior probabilities of the best and the next-best options, rather than by the posterior probability of the chosen (best) option alone, or by the overall uncertainty (entropy) of the posterior distribution. Our results upend the leading notion of decision confidence and instead suggest that confidence reflects the observer's subjective probability that they made the best possible decision.
    • Comments:
      Comment in: Trends Cogn Sci. 2020 Aug;24(8):590-591. (PMID: 32446639)
    • References:
      Persaud, N., McLeod, P. & Cowey, A. Post-decision wagering objectively measures awareness. Nat. Neurosci. 10, 257 (2007). (PMID: 1723777410.1038/nn184017237774)
      Van den Berg, R., Zylberberg, A., Kiani, R., Shadlen, M. N. & Wolpert, D. M. Confidence is the bridge between multi-stage decisions. Curr. Biol. 26, 3157–3168 (2016). (PMID: 27866891515475510.1016/j.cub.2016.10.021)
      Meyniel, F., Schlunegger, D. & Dehaene, S. The sense of confidence during probabilistic learning: a normative account. PLoS Comput. Biol. 11, e1004305 (2015). (PMID: 26076466446815710.1371/journal.pcbi.1004305)
      Bahrami, B. et al. Optimally interacting minds. Science 329, 1081–1085 (2010). (PMID: 20798320337158210.1126/science.1185718)
      Vaghi, M. M. et al. Compulsivity reveals a novel dissociation between action and confidence. Neuron 96, 348–354. e344 (2017). (PMID: 28965997564344310.1016/j.neuron.2017.09.006)
      Fleming, S. M. & Lau, H. C. How to measure metacognition. Front. Hum. Neurosci. 8, 443 (2014). (PMID: 25076880409794410.3389/fnhum.2014.00443)
      Mamassian, P. Visual confidence. Annu. Rev. Vis. Sci. 2, 459–481 (2016). (PMID: 2853235910.1146/annurev-vision-111815-11463028532359)
      Kepecs, A. & Mainen, Z. F. A computational framework for the study of confidence in humans and animals. Philos. Trans. R. Soc. Lond. B: Biol. Sci. 367, 1322–1337 (2012). (PMID: 10.1098/rstb.2012.0037)
      Yeung, N. & Summerfield, C. Metacognition in human decision-making: confidence and error monitoring. Philos. Trans. R. Soc. B 367, 1310–1321 (2012). (PMID: 10.1098/rstb.2011.0416)
      De Martino, B., Fleming, S. M., Garrett, N. & Dolan, R. J. Confidence in value-based choice. Nat. Neurosci. 16, 105 (2013). (PMID: 2322291110.1038/nn.327923222911)
      Lebreton, M., Abitbol, R., Daunizeau, J. & Pessiglione, M. Automatic integration of confidence in the brain valuation signal. Nat. Neurosci. 18, 1159 (2015). (PMID: 2619274810.1038/nn.406426192748)
      Polania, R., Woodford, M. & Ruff, C. C. Efficient coding of subjective value. Nat. Neurosci. 22, 134 (2019). (PMID: 3055947710.1038/s41593-018-0292-030559477)
      Pouget, A., Drugowitsch, J. & Kepecs, A. Confidence and certainty: distinct probabilistic quantities for different goals. Nat. Neurosci. 19, 366 (2016). (PMID: 26906503537847910.1038/nn.4240)
      Drugowitsch, J., Moreno-Bote, R. & Pouget, A. Relation between belief and performance in perceptual decision making. PloS ONE 9, e96511 (2014). (PMID: 24816801401603110.1371/journal.pone.0096511)
      Clarke, F. R., Birdsall, T. G. & Tanner, W. P. Jr Two types of ROC curves and definitions of parameters. J. Acoustical Soc. Am. 31, 629–630 (1959). (PMID: 10.1121/1.1907764)
      Galvin, S. J., Podd, J. V., Drga, V. & Whitmore, J. Type 2 tasks in the theory of signal detectability: discrimination between correct and incorrect decisions. Psychonomic Bull. Rev. 10, 843–876 (2003). (PMID: 10.3758/BF03196546)
      Peirce, C. S. & Jastrow, J. On small differences in sensation. (1884).
      Kepecs, A., Uchida, N., Zariwala, H. A. & Mainen, Z. F. Neural correlates, computation and behavioural impact of decision confidence. Nature 455, 227 (2008). (PMID: 1869021010.1038/nature0720018690210)
      Kiani, R. & Shadlen, M. N. Representation of confidence associated with a decision by neurons in the parietal cortex. Science 324, 759–764 (2009). (PMID: 19423820273893610.1126/science.1169405)
      Komura, Y., Nikkuni, A., Hirashima, N., Uetake, T. & Miyamoto, A. Responses of pulvinar neurons reflect a subject’s confidence in visual categorization. Nat. Neurosci. 16, 749 (2013). (PMID: 2366617910.1038/nn.339323666179)
      Sanders, J. I., Hangya, B. & Kepecs, A. Signatures of a statistical computation in the human sense of confidence. Neuron 90, 499–506 (2016). (PMID: 27151640535061410.1016/j.neuron.2016.03.025)
      Barthelmé, S. & Mamassian, P. Flexible mechanisms underlie the evaluation of visual confidence. Proc. Natl Acad. Sci. USA 107, 20834–20839 (2010). (PMID: 2107603610.1073/pnas.100770410721076036)
      Navajas, J. et al. The idiosyncratic nature of confidence. Nat. Hum. Behav. 1, 810 (2017). (PMID: 29152591568756710.1038/s41562-017-0215-1)
      Aitchison, L., Bang, D., Bahrami, B. & Latham, P. E. Doubly Bayesian analysis of confidence in perceptual decision-making. PLoS Comput. Biol. 11, e1004519 (2015). (PMID: 26517475462772310.1371/journal.pcbi.1004519)
      Adler, W. T. & Ma, W. J. Comparing Bayesian and non-Bayesian accounts of human confidence reports. PLoS Comput. Biol. 14, e1006572 (2018). (PMID: 30422974625856610.1371/journal.pcbi.1006572)
      Drugowitsch, J., Wyart, V., Devauchelle, A.-D. & Koechlin, E. Computational precision of mental inference as critical source of human choice suboptimality. Neuron 92, 1398–1411 (2016). (PMID: 2791645410.1016/j.neuron.2016.11.00527916454)
      Keshvari, S., Van den Berg, R. & Ma, W. J. Probabilistic computation in human perception under variability in encoding precision. PLoS ONE 7, e40216 (2012). (PMID: 22768258338702310.1371/journal.pone.0040216)
      Shen, S. & Ma, W. J. Variable precision in visual perception. Psychol. Rev. 126, 89–132 (2019). (PMID: 3033541110.1037/rev000012830335411)
      van den Berg, R., Yoo, A. H. & Ma, W. J. Fechner’s law in metacognition: A quantitative model of visual working memory confidence. Psychol. Rev. 124, 197 (2017). (PMID: 28221087532157010.1037/rev0000060)
      Akaike, H. A new look at the statistical model identification. IEEE Transactions on Automatic Control. 19, 716–723 (1974). (PMID: 10.1109/TAC.1974.1100705)
      Schwarz, G. Estimating the dimension of a model. Ann. Stat. 6, 461–464 (1978). (PMID: 10.1214/aos/1176344136)
      Kiani, R., Corthell, L. & Shadlen, M. N. Choice certainty is informed by both evidence and decision time. Neuron 84, 1329–1342 (2014). (PMID: 25521381427119110.1016/j.neuron.2014.12.015)
      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). (PMID: 2586811310.1016/j.cogpsych.2015.01.00225868113)
      Pleskac, T. J. & Busemeyer, J. R. Two-stage dynamic signal detection: a theory of choice, decision time, and confidence. Psychol. Rev. 117, 864 (2010). (PMID: 2065885610.1037/a001973720658856)
      Yu, S., Pleskac, T. J. & Zeigenfuse, M. D. Dynamics of postdecisional processing of confidence. J. Exp. Psychol.: Gen. 144, 489 (2015). (PMID: 10.1037/xge0000062)
      Navajas, J., Bahrami, B. & Latham, P. E. Post-decisional accounts of biases in confidence. Curr. Opin. Behav. Sci. 11, 55–60 (2016). (PMID: 10.1016/j.cobeha.2016.05.005)
      Koizumi, A., Maniscalco, B. & Lau, H. Does perceptual confidence facilitate cognitive control? Atten., Percept., Psychophys. 77, 1295–1306 (2015). (PMID: 10.3758/s13414-015-0843-3)
      Zylberberg, A., Barttfeld, P. & Sigman, M. The construction of confidence in a perceptual decision. Front Integr. Neurosci. 6, 2359–2374 (2012). (PMID: 10.3389/fnint.2012.00079)
      Peters, M. A. et al. Perceptual confidence neglects decision-incongruent evidence in the brain. Nat. Hum. Behav. 1, 0139 (2017). (PMID: 29130070567513310.1038/s41562-017-0139)
      Maniscalco, B. & Lau, H. A signal detection theoretic approach for estimating metacognitive sensitivity from confidence ratings. Conscious. Cognition 21, 422–430 (2012). (PMID: 10.1016/j.concog.2011.09.021)
      Desender, K., Boldt, A. & Yeung, N. Subjective confidence predicts information seeking in decision making. Psychol. Sci. 29, 761–778 (2018). (PMID: 2960841110.1177/095679761774477129608411)
      Brown, S., Steyvers, M. & Wagenmakers, E.-J. Observing evidence accumulation during multi-alternative decisions. J. Math. Psychol. 53, 453–462 (2009). (PMID: 10.1016/j.jmp.2009.09.002)
      Markant, D. B., Settles, B. & Gureckis, T. M. Self directed learning favors local, rather than global, uncertainty. Cogn. Sci. 40, 100–120 (2016). (PMID: 2578991810.1111/cogs.1222025789918)
      Kahneman, D. & Tversky, A. Prospect theory: An analysis of decision under risk. Econometrica. 47, 263–292 (1979). (PMID: 10.2307/1914185)
      Carandini, M. & Heeger, D. J. Normalization as a canonical neural computation. Nat. Rev. Neurosci. 13, 51–62 (2012). (PMID: 10.1038/nrn3136)
      Louie, K., Grattan, L. E. & Glimcher, P. W. Reward value-based gain control: divisive normalization in parietal cortex. J. Neurosci. 31, 10627–10639 (2011). (PMID: 21775606328550810.1523/JNEUROSCI.1237-11.2011)
      Stengård, E., Van & den Berg, R. Imperfect Bayesian inference in visual perception. PLoS Comput. Biol. 15, e1006465 (2019). (PMID: 30998675647273110.1371/journal.pcbi.1006465)
      Ratcliff, R., Smith, P. L., Brown, S. D. & McKoon, G. Diffusion decision model: Current issues and history. Trends Cogn. Sci. 20, 260–281 (2016). (PMID: 269527392695273910.1016/j.tics.2016.01.007)
      Ratcliff, R. & Starns, J. J. Modeling confidence judgments, response times, and multiple choices in decision making: recognition memory and motion discrimination. Psychol. Rev. 120, 697 (2013). (PMID: 23915088410612710.1037/a0033152)
      Ratcliff, R. & Starns, J. J. Modeling confidence and response time in recognition memory. Psychol. Rev. 116, 59 (2009). (PMID: 19159148269389910.1037/a0014086)
      Vickers, D. Decision processes in visual perception. (Academic Press, 1979).
      Vickers, D. Where does the balance of evidence lie with respect to confidence? In Proceedings of the seventeenth annual meeting of the international society for psychophysics. pp. 148–153 (Lengerich, Germany: Pabst Science Publishers, 2001).
      Vickers, D. & Lee, M. D. Dynamic models of simple judgments: I. Properties of a self-regulating accumulator module. Nonlinear Dynamics. Psychol., Life Sci. 2, 169–194 (1998).
      Folke, T., Jacobsen, C., Fleming, S. M. & De Martino, B. Explicit representation of confidence informs future value-based decisions. Nature Human. Behaviour 1, 0002 (2017).
      Odegaard, B. et al. Superior colliculus neuronal ensemble activity signals optimal rather than subjective confidence. Proceedings of the National Academy of Sciences, 115, E1588–E1597 (2018). (PMID: 10.1073/pnas.1711628115)
      Churchland, A. K., Kiani, R. & Shadlen, M. N. Decision-making with multiple alternatives. Nat. Neurosci. 11, 693 (2008). (PMID: 18488024245322610.1038/nn.2123)
      Churchland, A. K. & Ditterich, J. New advances in understanding decisions among multiple alternatives. Curr. Opin. Neurobiol. 22, 920–926 (2012). (PMID: 22554881342260710.1016/j.conb.2012.04.009)
      Ditterich, J. A comparison between mechanisms of multi-alternative perceptual decision making: ability to explain human behavior, predictions for neurophysiology, and relationship with decision theory. Front. Neurosci. 4, 184 (2010). (PMID: 21152262299939510.3389/fnins.2010.00184)
      Hampton, R. R. Rhesus monkeys know when they remember. Proc. Natl Acad. Sci. 98, 5359–5362 (2001). (PMID: 1127436010.1073/pnas.07160099811274360)
      Foote, A. L. & Crystal, J. D. Metacognition in the rat. Curr. Biol. 17, 551–555 (2007). (PMID: 17346969186184510.1016/j.cub.2007.01.061)
      Acerbi, L., Wolpert, D. M. & Vijayakumar, S. Internal representations of temporal statistics and feedback calibrate motor-sensory interval timing. PLoS computational Biol. 8, e1002771 (2012). (PMID: 10.1371/journal.pcbi.1002771)
      van den Berg, R., Awh, E. & Ma, W. J. Factorial comparison of working memory models. Psychological Rev. 121, 124 (2014). (PMID: 10.1037/a0035234)
      Daunizeau, J., Preuschoff, K., Friston, K. & Stephan, K. Optimizing experimental design for comparing models of brain function. PLoS computational Biol. 7, e1002280 (2011). (PMID: 10.1371/journal.pcbi.1002280)
      Acerbi, L. & Ma, W. J. Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search. In Advances in Neural Information Processing Systems. pp. 1836–1846 (2017).
    • Publication Date:
      Date Created: 20200426 Date Completed: 20200810 Latest Revision: 20210424
    • Publication Date:
      20240829
    • Accession Number:
      PMC7181620
    • Accession Number:
      10.1038/s41467-020-15581-6
    • Accession Number:
      32332712