Emotion and decision-making: Affect-driven belief systems in anxiety and depression
Journal
Trends in Cognitive Sciences
Journal Volume
16
Journal Issue
9
Pages
476-483
Date Issued
2012
Author(s)
Paulus M.P
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 that link emotion and decision-making, and focus on research with anxious or depressed individuals to show 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 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. © 2012.
SDGs
Other Subjects
Bayesian networks; Behavioral research; Markov processes; Bayesian approaches; Belief systems; Daily lives; Emotion processing; Partially observable Markov decision process; Probabilistic representation; Theoretical approach; Decision making; ambivalence; anxiety; arousal; Bayesian learning; conceptual framework; decision making; depression; emotion; review
Type
review