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Selective use of new information is crucial for adaptive decision-making. Combining a gamble bidding task with assessing cortical responses using functional near-infrared spectroscopy (fNIRS), we investigated potential effects of information valence on behavioral and neural processes of belief and value updating during uncertainty reduction in young adults. By modeling changes in the participants' expressed subjective values using a Bayesian model, we dissociated processes of (i) updating beliefs about statistical properties of the gamble, (ii) updating values of a gamble based on new information about its winning probabilities, as well as (iii) expectancy violation. The results showed that participants used new information to update their beliefs and values about the gambles in a quasi-optimal manner, as reflected in the selective updating only in situations with reducible uncertainty. Furthermore, their updating was valence-dependent: information indicating an increase in winning probability was underweighted, whereas information about a decrease in winning probability was updated in good agreement with predictions of the Bayesian decision theory. Results of model-based and moderation analyses showed that this valence-dependent asymmetry was associated with a distinct contribution of expectancy violation, besides belief updating, to value updating after experiencing new positive information regarding winning probabilities. In line with the behavioral results, we replicated previous findings showing involvements of frontoparietal brain regions in the different components of updating. Furthermore, this study provided novel results suggesting a valence-dependent recruitment of brain regions. Individuals with stronger oxyhemoglobin responses during value updating was more in line with predictions of the Bayesian model while integrating new information that indicates an increase in winning probability. Taken together, this study provides first results showing expectancy violation as a contributing factor to sub-optimal valence-dependent updating during uncertainty reduction and suggests limitations of normative Bayesian decision theory., Competing Interests: Declaration of Competing Interest Authors declare that they have no conflict of interest., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Human decisions are often influenced by emotions. An economically relevant example is the role of fear in generating loss aversion. Previous research implicates the amygdala as a key brain structure in the experience of fear and loss aversion. The neural mechanism behind emotional influences on loss aversion is, however, unclear. To address this, we measured brain activation with functional magnetic resonance imaging (fMRI) while participants made decisions about monetary gambles after viewing fearful or neutral faces. We observed that loss aversion following the presentation of neutral faces was mainly predicted by greater deactivations for prospective losses (relative to activations for prospective gains) in several brain regions, including the amygdala. By contrast, increases in loss aversion following the presentation of fearful faces were mainly predicted by greater activations for prospective losses. These findings suggest a fear-induced shift from positive to negative value coding that reflects a context-dependent involvement of distinct valuation processes., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)