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bioRxiv · 10.1101/017400

A mathematical framework for statistical decision confidence

Balázs Hangya·Joshua I. Sanders·Adam Kepecs
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Abstract

Decision confidence is a forecast about the probability that a decision will be correct. Confidence can be framed as an objective mathematical quantity the Bayesian posterior probability, providing a formal definition of statistical decision confidence. Here we use this definition as a starting point to develop a normative statistical framework for decision confidence. We analytically prove interrelations between statistical decision confidence and other observable decision measures. Among these is a counterintuitive property of confidence that the lowest average confidence occurs when classifiers err in the presence of the strongest evidence. These results lay the foundations for a mathematically rigorous treatment of decision confidence that can lead to a common framework for understanding confidence across different research domains, from human behavior to neural representations.

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Balázs Hangya, Joshua I. Sanders, Adam Kepecs. 2015-04-01. A mathematical framework for statistical decision confidence. https://doi.org/10.1101/017400

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