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The formation of preference in risky choice

  • Moshe Glickman
  • , Orian Sharoni
  • , Dino J. Levy
  • , Ernst Niebur
  • , Veit Stuphorn
  • , Marius Usher
  • Tel Aviv University
  • Johns Hopkins University

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

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.

Original languageEnglish
Article numbere1007201
JournalPLoS Computational Biology
Volume15
Issue number8
DOIs
StatePublished - Aug 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
Copyright: © 2019 Glickman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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