We assess whether a cardinal model can be used to relate neural observables to stochastic choice behaviour. We develop a general empirical framework for relating any neural observable to choice prediction, and propose a means of bench-marking their predictive power. In a previous study,...

Weather, in particular the intensity and duration of sunshine (luminance), has been shown to significantly affect market outcomes. Yet, because of the complexity of market interactions we do not know how human behavior is affected by luminance in a way that could inform microeconomic choice...

Abstract Recent advances in neuroscience suggest a utility-like calculation is involved in how the brain makes choices, and that this calculation may use a computation known as divisive normalization. While this tells us how the brain makes choices, it is not immediately evident why the brain...

We present a novel descriptive model of choice that achieves an efficient representation anchored to how the brain represents value. An individual's behavior is fully described by two primitives: an individual's "reward expectation'' and a free parameter we call "predisposition''. We demonstrate...

Prior information is invaluable to decision makers facing noisy evidence, allowing them to increase their chances of choosing the best option. Yet human choice behavior often exhibits base-rate neglect. In order to better understand the mechanisms underlying such sub-optimal behaviors, we...

Prospect theory, widely used descriptively for decisions under both risk and certainty, presumes concave utility over “gains” and convex utility over “losses”; a pattern widely seen in lottery tasks. Although such gain-loss asymmetry is also widely used to model riskless choices, limited...

Many studies document failures of expected utility’s key assumption, the independence axiom. Here, we show that independence can be decomposed into two distinct axioms – betweenness and homotheticity – and that these two axioms are necessary and sufficient for independence. Thus,...

The probability triangle (also called the Marschak-Machina triangle) allows for compact and intuitive depictions of risk preferences. Here, we develop an analogous tool for choice under uncertainty – the ambiguity triangle – and show that indifference curves in this triangle capture...

The probability triangle (also called the Marschak-Machina triangle) allows for compact and intuitive depictions of risk preferences. Here, we develop an analogous tool for choice under uncertainty - the ambiguity triangle - and show that indifference curves in this triangle capture preferences...

The probability triangle (also called the Marschak-Machina triangle) allows for compact and intuitive depictions of risk preferences. Here, we develop an analogous tool for choice under uncertainty - the ambiguity triangle - and show that indifference curves in this triangle capture preferences...