Emotion and decision-making: affect-driven belief systems in anxiety and depression
Identifieur interne : 002182 ( Ncbi/Merge ); précédent : 002181; suivant : 002183Emotion and decision-making: affect-driven belief systems in anxiety and depression
Auteurs : Martin P. Paulus [États-Unis] ; Angela J. Yu [États-Unis]Source :
- Trends in cognitive sciences [ 1364-6613 ] ; 2012.
Abstract
Emotion processing and decision-making are integral aspects of daily life. However, our understanding of the interaction between these constructs is limited. In this review, we summarize theoretical approaches to the link between emotion and decision-making, and focus on research with anxious or depressed individuals that reveals how emotions can interfere with decision-making. We integrate the emotional framework based on valence and arousal with a Bayesian approach to decision-making in terms of probability and value processing. We then discuss how studies of individuals with emotional dysfunctions provide evidence that alterations of decision-making can be viewed in terms of altered probability and value computation. We argue that the probabilistic representation of belief states in the context of partially observable Markov decision processes provides a useful approach to examine alterations in probability and value representation in individuals with anxiety and depression and outline the broader implications of this approach.
Url:
DOI: 10.1016/j.tics.2012.07.009
PubMed: 22898207
PubMed Central: 3446252
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PMC:3446252Le document en format XML
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<front><div type="abstract" xml:lang="en"><p id="P2">Emotion processing and decision-making are integral aspects of daily life. However, our understanding of the interaction between these constructs is limited. In this review, we summarize theoretical approaches to the link between emotion and decision-making, and focus on research with anxious or depressed individuals that reveals how emotions can interfere with decision-making. We integrate the emotional framework based on valence and arousal with a Bayesian approach to decision-making in terms of probability and value processing. We then discuss how studies of individuals with emotional dysfunctions provide evidence that alterations of decision-making can be viewed in terms of altered probability and value computation. We argue that the probabilistic representation of belief states in the context of partially observable Markov decision processes provides a useful approach to examine alterations in probability and value representation in individuals with anxiety and depression and outline the broader implications of this approach.</p>
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Department of Psychiatry, University of California San Diego, La Jolla, CA 92037, USA</aff>
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Psychiatry Service, VA San Diego Healthcare System, La Jolla, CA 92161, USA</aff>
<aff id="A3"><label>3</label>
Department of Cognitive Science, MC 0515, University of California, San Diego, La Jolla, CA 92093, USA</aff>
<author-notes><corresp id="FN1">Corresponding author: Paulus, M.P. (<email>mpaulus@ucsd.edu</email>
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<volume>16</volume>
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<fpage>476</fpage>
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<permissions><copyright-statement>© 2012 Elsevier Ltd. All rights reserved.</copyright-statement>
<copyright-year>2012</copyright-year>
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<abstract><p id="P2">Emotion processing and decision-making are integral aspects of daily life. However, our understanding of the interaction between these constructs is limited. In this review, we summarize theoretical approaches to the link between emotion and decision-making, and focus on research with anxious or depressed individuals that reveals how emotions can interfere with decision-making. We integrate the emotional framework based on valence and arousal with a Bayesian approach to decision-making in terms of probability and value processing. We then discuss how studies of individuals with emotional dysfunctions provide evidence that alterations of decision-making can be viewed in terms of altered probability and value computation. We argue that the probabilistic representation of belief states in the context of partially observable Markov decision processes provides a useful approach to examine alterations in probability and value representation in individuals with anxiety and depression and outline the broader implications of this approach.</p>
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