Asymmetric Effects of Favorable and Unfavorable Information on Decision Making Under Ambiguity

Most daily decisions involve uncertainty about outcome probabilities arising from incomplete knowledge, i.e., ambiguity. We explore how the addition of partial information affects these types of choices using theoretical and empirical methods. Our experiments in both gain and loss domains demonstrate that when such information supports a favorable outcome, it strongly increases valuation of an ambiguous financial prospect. However, when information supports an unfavorable outcome, it has significantly less impact. We find that two mechanisms drive this asymmetry. First, unfavorable information decreases estimates of a good outcome occurring but also reduces aversive uncertainty. These factors act in opposition, minimizing the effects of unfavorable information. Second, when information can be subjectively interpreted, unfavorable information is less likely to be integrated into evaluations. Our findings reveal mechanisms not captured by traditional models of decision making under uncertainty and highlight the importance of increasing the salience of unfavorable information in uncertain contexts to promote unbiased decision making. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2015.2233 . This paper was accepted by Teck-Hua Ho, behavioral economics

Dissociable components of the reward circuit are involved in appraisal versus choice.

People can evaluate a set of options as a whole, or they can approach those same options with the purpose of making a choice between them. A common network has been implicated across these two types of evaluations, including regions of ventromedial prefrontal cortex and the posterior midline. We test the hypothesis that sub-components of this reward circuit are differentially involved in triggering more automatic appraisal of one's options (Dorsal Value Network) versus explicitly comparing between those options (Ventral Value Network). Participants undergoing fMRI were instructed to appraise how much they liked a set of products (Like) or to choose the product they most preferred (Choose). Activity in the Dorsal Value Network consistently tracked set liking, across both task-relevant (Like) and task-irrelevant (Choose) trials. In contrast, the Ventral Value Network was particularly sensitive to evaluation condition (more active during Choose than Like trials). Within vmPFC, anatomically distinct regions were dissociated in their sensitivity to choice (ventrally, in medial OFC) versus appraisal (dorsally, in pregenual ACC). Dorsal regions additionally tracked decision certainty across both types of evaluation. These findings suggest that separable mechanisms drive decisions about how good one's options are versus decisions about which option is best