The Dynamics of Decision Making in Risky Choice: An Eye-Tracking Analysis

In the last years, research on risky choice has moved beyond analyzing choices only. Models have been suggested that aim to describe the underlying cognitive processes and some studies have tested process predictions of these models. Prominent approaches are evidence accumulation models such as deci...

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Published in:Frontiers in psychology Vol. 3; p. 335
Main Authors: Fiedler, Susann, Glöckner, Andreas
Format: Journal Article
Language:English
Published: Switzerland Frontiers Research Foundation 01.01.2012
Frontiers Media S.A
Subjects:
Arousal
Decision Making
Eye-tracking
Heuristics
Psychology
Risky choices
parallel constraint satisfaction
decision field theory
heuristics
eye tracking
gaze-cascade effect
risky choices
arousal
ISSN:1664-1078, 1664-1078
Online Access:Get full text
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Summary:In the last years, research on risky choice has moved beyond analyzing choices only. Models have been suggested that aim to describe the underlying cognitive processes and some studies have tested process predictions of these models. Prominent approaches are evidence accumulation models such as decision field theory (DFT), simple serial heuristic models such as the adaptive toolbox, and connectionist approaches such as the parallel constraint satisfaction (PCS) model. In two studies involving measures of attention and pupil dilation, we investigate hypotheses derived from these models in choices between two gambles with two outcomes each. We show that attention to an outcome of a gamble increases with its probability and its value and that attention shifts toward the subsequently favored gamble after about two thirds of the decision process, indicating a gaze-cascade effect. Information search occurs mostly within-gambles, and the direction of search does not change over the course of decision making. Pupil dilation, which reflects both cognitive effort and arousal, increases during the decision process and increases with mean expected value. Overall, the results support aspects of automatic integration models for risky choice such as DFT and PCS, but in their current specification none of them can account for the full pattern of results.
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Reviewed by: Joseph G. Johnson, Miami University, USA; Neil Stewart, University of Warwick, UK; Ian Krajbich, University of Zurich, Switzerland
This article was submitted to Frontiers in Cognitive Science, a specialty of Frontiers in Psychology.
Edited by: Marius Usher, Tel-Aviv University, Israel
ISSN:1664-1078
1664-1078
DOI:10.3389/fpsyg.2012.00335