The Neural Basis of Risky Choice with Affective Outcomes

Abstract

Both normative and many descriptive theories of decision making under risk are based on the notion that outcomes are weighted by their probability, with subsequent maximization of the (subjective) expected outcome. Numerous investigations from psychology, economics, and neuroscience have produced evidence consistent with this notion. However, this research has typically investigated choices involving relatively affect-poor, monetary outcomes. We compared choice in relatively affect-poor, monetary lottery problems with choice in relatively affect-rich medical decision problems. Computational modeling of behavioral data and model-based neuroimaging analyses provide converging evidence for substantial differences in the respective decision mechanisms. Relative to affect-poor choices, affect-rich choices yielded a more strongly curved probability weighting function of cumulative prospect theory, thus signaling that the psychological impact of probabilities is strongly diminished for affect-rich outcomes. Examining task-dependent brain activation, we identified a region-by-condition interaction indicating qualitative differences of activation between affect-rich and affect-poor choices. Moreover, brain activation in regions that were more active during affect-poor choices (e.g., the supramarginal gyrus) correlated with individual trial-by-trial decision weights, indicating that these regions reflect processing of probabilities. Formal reverse inference Neurosynth meta-analyses suggested that whereas affect-poor choices seem to be based on brain mechanisms for calculative processes, affect-rich choices are driven by the representation of outcomes’ emotional value and autobiographical memories associated with them. These results provide evidence that the traditional notion of expectation maximization may not apply in the context of outcomes laden with affective responses, and that understanding the brain mechanisms of decision making requires the domain of the decision to be taken into account.

The gap between medical and monetary choices under risk persists in decisions for others

“…Differences in decision strategies and cognitive processes between choices with medical and monetary prospects have been systematically examined in several studies (Lejarraga et al, 2016;Pachur et al, 2014;Pachur & Galesic, 2013;Suter et al, 2016Suter et al, , 2015. These studies suggest that in the medical domain compared with the monetary domain, people focus more on avoiding the worst outcome, largely disregarding the probability of the outcomes.…”

“…When faced with medical rather than monetary prospects, however, people seem to rely on a substantially different mechanism. Specifically, people often seem to neglect probability information and to rely on simpler, heuristic decision strategies (Lejarraga, Pachur, Frey, & Hertwig, ; Pachur & Galesic, ; Pachur, Hertwig, & Wolkewitz, ; Suter, Pachur, & Hertwig, ; Suter, Pachur, Hertwig, Endestad, & Biele, ).…”

Understanding clinical and non-clinical decisions under uncertainty: a scenario-based survey

“…One possible explanation for the differences in decision patterns and risk preference across domains may come from the affect involved in healthcare-related decisions [28]. Several behavioral studies have identified differences in decision making between affect-rich and affect-poor tasks [29–33].…”

“…This distinction is important because multiple models of decision making under risk share the common notion that outcomes are weighted by their probability, maximizing the expected outcome. However, when faced with emotion or affect-charged decisions, evidence suggests that people systematically choose the optimal option less often [28]. And others have suggested that the impact of probability information may be attenuated in affect-rich choices [34].…”

Rabin's paradox for health outcomes

“…There it has had vast implications, as citation scores show. It is well known that preferences for health outcomes may differ from decisions for financial outcomes (even at a neurological level, see Suter, Pachur, Hertwig, Endestad, & Biele, ). Such differences have been observed for time preferences (e.g., Attema, Bleichrodt, L'Haridon, Peretti‐Watel, & Seror, ; Chapman, ), ambiguity preferences (e.g., Curley, Eraker, & Yates, ), and, most relevant to our purposes, risk preferences (e.g., Suter, Pachur, & Hertwig, ; Weber, Blais, & Betz, ).…”