Moral decision-making in context: Behavioral and neural processes underlying allocations based on need, merit, and equality.

How to fairly allocate goods is a key issue of social decision-making. Extensive research demonstrates that people do not selfishly maximize their own benefits, but instead also consider how others are affected. However, most accounts of the psychological processes underlying fairness-related behavior implicitly assume that assessments of fairness are somewhat stable. In this paper, we present results of a novel task, the Re-Allocation Game, in which two players receive an allocation determined by the computer and, on half of the trials, one player has the subsequent possibility to change this allocation. Importantly, prior to the receipt of the allocation, players were shown either their respective financial situations, their respective performance on a previous simple task, or random information, while being scanned using functional neuroimaging. As expected, our results demonstrate when given the opportunity, participants allocated on average almost half the money to anonymous others. However, our findings further show that participants used the provided information in a dynamic manner, revealing the underlying principle based on which people re-allocate money - namely based on merit, need, or equality - switches dynamically. On the neural level, we identified activity in the right and left dorsolateral prefrontal cortices related to context-independent inequity and context-dependent fairness information respectively when viewing the computer-generated allocations. At the same time, activity in the temporoparietal and precuneus represented these different types of fairness-related information in adjacent and partially overlapping clusters. Finally, we observed that the activity pattern in the precuneus and putamen was most clearly related to participants' subsequent re-allocation decisions. Together, our findings suggest that participants judge an allocation as fair or unfair using a network associated with cognitive control and theory-of-mind, while dynamically switching between what might constitute a fair allocation in a particular context.

Computational modeling of social decision-making.

Social decision-making is guided by a complex set of social norms. Computational modeling can play a significant role in enriching our understanding of these norms and how precisely they direct social choices. Here, we highlight three major advantages to using computational modeling, particularly models derived from Utility Theory, in the study of social norms. We illustrate how such models can help generate detailed processes of decision-making, enforce theoretical precision by delineating abstract concepts, and unpack when, and why, people adhere to specific social norms. For each benefit, we discuss a recent study which has employed modeling in the service of assessing the role of norms in decision-making, collectively revealing how computational modeling enables better prediction, description, and explanation of important social choices.