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A Computational Framework for the Study of Confidence Across Species

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The Cognitive Neuroscience of Metacognition

Abstract

Confidence judgments, the self-assessment of the quality of a subject’s knowledge, are considered a central example of metacognition. Prima facie, introspection, and self-report appear the only way to access the subjective sense of confidence or uncertainty. Could confidence be also studied in nonhuman animals so one could probe its neural substrates? Indeed, behavioral paradigms that incentivize animals to evaluate and act upon their own confidence can yield implicit reports of confidence. Here, we suggest that a computational approach can clarify the issues involved in interpreting these tasks and provide a much-needed springboard for advancing the scientific understanding of confidence. We first review relevant theories of probabilistic inference and decision making. We then critically discuss behavioral tasks employed to measure confidence in animals and show how quantitative models can help to constrain the computational strategies underlying confidence-reporting behaviors. In our view, post-decision wagering tasks with continuous measures of confidence appear to offer the best available metrics of confidence. Since behavioral reports alone provide a limited window into mechanism, we argue that progress calls for measuring the neural representations and identifying the computations underlying confidence reports. We present a case study using such a computational approach to study the neural correlates of decision confidence in rats. This work shows that confidence assessments may be considered higher order, but can be generated using elementary neural computations that are available to a wide range of species. Finally, we discuss the relationship of confidence judgments to the broader behavioral uses of confidence and uncertainty.

This chapter is adapted from: Kepecs A, Mainen ZF (2012) A computational framework for the study of confidence in humans and animals. Phil Trans R Soc B 367:1322–1337

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Acknowledgments

We are grateful to our collaborators and members of our groups for discussions. Preparation of this article was supported by the Klingenstein, Sloan, Swartz, and Whitehall Foundations to A.K.

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Authors and Affiliations

  1. Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York, 11724, USA

    Adam Kepecs

  2. Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Av. Brasília s/n, 1400-038, Lisbon, Portugal

    Zachary F. Mainen

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Correspondence to Adam Kepecs .

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Editors and Affiliations

  1. Center for Neural Science, New York University, New York, New York, USA

    Stephen M. Fleming

  2. Aarhus University Hospital, Aarhus C, Denmark

    Christopher D. Frith

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Kepecs, A., Mainen, Z.F. (2014). A Computational Framework for the Study of Confidence Across Species. In: Fleming, S., Frith, C. (eds) The Cognitive Neuroscience of Metacognition. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45190-4_6

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