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Loss Aversion Correlates With the Propensity to Deploy Model-Based Control

Solway, A; Lohrenz, T; Montague, PR; (2019) Loss Aversion Correlates With the Propensity to Deploy Model-Based Control. Frontiers in Neuroscience , 13 , Article 915. 10.3389/fnins.2019.00915. Green open access

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Abstract

Reward-based decision making is thought to be driven by at least two different types of decision systems: a simple stimulus–response cache-based system which embodies the common-sense notion of “habit,” for which model-free reinforcement learning serves as a computational substrate, and a more deliberate, prospective, model-based planning system. Previous work has shown that loss aversion, a well-studied measure of how much more on average individuals weigh losses relative to gains during decision making, is reduced when participants take all possible decisions and outcomes into account including future ones, relative to when they myopically focus on the current decision. Model-based control offers a putative mechanism for implementing such foresight. Using a well-powered data set (N = 117) in which participants completed two different tasks designed to measure each of the two quantities of interest, and four models of choice data for these tasks, we found consistent evidence of a relationship between loss aversion and model-based control but in the direction opposite to that expected based on previous work: loss aversion had a positive relationship with model-based control. We did not find evidence for a relationship between either decision system and risk aversion, a related aspect of subjective utility.

Type: Article
Title: Loss Aversion Correlates With the Propensity to Deploy Model-Based Control
Open access status: An open access version is available from UCL Discovery
DOI: 10.3389/fnins.2019.00915
Publisher version: https://doi.org/10.3389/fnins.2019.00915
Language: English
Additional information: Copyright © 2019 Solway, Lohrenz and Montague. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (http://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Keywords: reinforcement learning, model-based, planning, neuroeconomics, subjective utility, loss aversion
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
URI: https://discovery.ucl.ac.uk/id/eprint/10087104
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