The formation of preference in risky choice

A key question in decision-making is how people integrate amounts and probabilities to form preferences between risky alternatives. Here we rely on the general principle of integration-to-boundary to develop several biologically plausible process models of risky-choice, which account for both choices and response-times. These models allowed us to contrast two influential competing theories: i) within-alternative evaluations, based on multiplicative interaction between amounts and probabilities, ii) within-attribute comparisons across alternatives. To constrain the preference formation process, we monitored eye-fixations during decisions between pairs of simple lotteries, designed to systematically span the decision-space. The behavioral results indicate that the participants' eye-scanning patterns were associated with risk-preferences and expected-value maximization. Crucially, model comparisons showed that within-alternative process models decisively outperformed within-attribute ones, in accounting for choices and response-times. These findings elucidate the psychological processes underlying preference formation when making risky-choices, and suggest that compensatory, within-alternative integration is an adaptive mechanism employed in human decision-making.Author summary: Decision-making under risk requires a selection between alternatives, such as lotteries, which offer a reward with a specified probability. Human decision between such alternatives is at the center of the normative decision theory, which assumes that decisions are rationally made by forming a value for each alternative and selecting the alternative with the highest value. To this day, there is still a considerable debate on how such values are computed. While the normative theory assumes that values of the alternatives reflect the statistically expected rewards, more recent theories have argued that alternative-values are not computed, and choices are only based on sequentially comparing the alternatives on amounts or on probabilities. Here, we carried out an experimental investigation of risky decision-making, in which participants chose between pairs of simple lottery alternatives that systematically span a range of probabilities and amounts, while we tracked their eye positions during the decision-making process. We found that the participants are sensitive to the expected-utility of the alternatives, as predicted by the normative decision theories, but they also exhibit risk-biases that correlate with the eye-scanning patterns. We then carry out computational modeling, comparing preference-formation models on their ability to account for both choices and their reaction-times. The results provide strong support for normative models, which assume that the values of the alternative are computed via a multiplicative function of the amounts and probabilities. These results suggest that humans are closer to normative principles than previously assumed, and motivate further investigation into the neural mechanism that mediates these multiplicative computations.