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Decision-Making, Pro-variance Biases and Mood-Related Traits

Lin, Wanjun; Dolan, Raymond J; (2024) Decision-Making, Pro-variance Biases and Mood-Related Traits. Computational Psychiatry , 8 (1) pp. 142-158. 10.5334/cpsy.114. Green open access

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Abstract

In value-based decision-making there is wide behavioural variability in how individuals respond to uncertainty. Maladaptive responses to uncertainty have been linked to a vulnerability to mental illness, for example, between risk aversion and affective disorders. Here, we examine individual differences in risk sensitivity when subjects confront options drawn from different value distributions, where these embody the same or different means and variances. In simulations, we show that a model that learns a distribution using Bayes' rule and reads out different parts of the distribution under the influence of a risk-sensitive parameter (Conditional Value at Risk, CVaR) predicts how likely an agent is to prefer a broader over a narrow distribution (pro-variance bias/risk-seeking) under the same overall means. Using empirical data, we show that CVaR estimates correlate with participants' pro-variance biases better than a range of alternative parameters derived from other models. Importantly, across two independent samples, CVaR estimates and participants' pro-variance bias negatively correlated with trait rumination, a common trait in depression and anxiety. We conclude that a Bayesian-CVaR model captures individual differences in sensitivity to variance in value distributions and task-independent trait dispositions linked to affective disorders.

Type: Article
Title: Decision-Making, Pro-variance Biases and Mood-Related Traits
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.5334/cpsy.114
Publisher version: http://dx.doi.org/10.5334/cpsy.114
Language: English
Additional information: COPYRIGHT: © 2024 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/ licenses/by/4.0/.
Keywords: Bayesian, Conditional Value-at-Risk, Pro-variance bias, Risk-seeking, Rumination, Uncertainty
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
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/10196702
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