Key Points
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Two historically separate lines of research on social versus non-social decision making are converging in a focus on neural value computations. These value signals may reflect neural mechanisms that enable unified control of behaviour across social and non-social contexts.
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Two competing theoretical accounts propose that neural value computations underlying both types of choice may either be performed by the very same neurons — therefore providing a 'common motivational currency' for social and non-social information — or that they may involve different, functionally specialized neuronal populations. There is evidence for both accounts, but existing methodical limitations preclude unambiguous support for just one of them.
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Social versus non-social choices differ in terms of functional connectivity between regions that are involved in representing value signals and other brain areas that specifically encode social-cognitive functions. This suggests that social and non-social choices mainly differ in the information that is used as input for similar neural value computations.
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Neural value computations and associated patterns of functional connectivity have been documented for social decisions in three distinct classes of situation that differ with respect to the target and the reference frame of valuation. These classes respectively reflect situations in which interactions with other people are rewarding to the agent, situations in which agents assess value vicariously for other people they observe, and situations in which agents behave in line with abstract social principles.
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Studies in animal models suggest that some of the social neural value signals are also computed in the non-human primate brain but by different neuronal populations than comparable non-social value signals.
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A few results from clinical and neural intervention studies show that disruptions of some of these value signals can change social decision making, suggesting an important causal role of these signals in the control of behaviour in social contexts.
Abstract
How does our brain choose the best course of action? Choices between material goods are thought to be steered by neural value signals that encode the rewarding properties of the choice options. Social decisions, by contrast, are traditionally thought to rely on neural representations of the self and others. However, recent studies show that many types of social decisions may also involve neural value computations. This suggests a unified mechanism for motivational control of behaviour that may incorporate both social and non-social factors. In this Review, we outline a theoretical framework that may help to identify possible overlaps and differences between the neural processes that guide social and non-social decision making.
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Acknowledgements
Preparation of this article was made possible by funding from the Swiss National Science Foundation (SNSF) to C.C.R. and E.F. E.F. also acknowledges support from the European Research Council Grant on the “Foundations of Economic Preferences”. The authors thank P. Tobler, S. Huettel and two anonymous referees for helpful comments.
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Glossary
- Delay discounting
-
The systematic decrease in a given item's value with increasing delay until it will be received. Excessive delay discounting is often thought to underlie impulsive choices.
- Trust game
-
An experimental paradigm to measure trust between anonymous players. Player 1 decides how much of his or her money to transfer to player 2. The transferred amount is multiplied by a factor >1 before player 2 decides how much money to give back to player 1, thus honouring the trust evident in the initial transfer.
- Reciprocity
-
A behavioural strategy whereby an individual responds to another agent's kind (or hostile) action with a kind (or hostile) action. Reciprocity lies at the heart of 'tit-for-tat' and is often thought to be an important motivation for altruism.
- Priors
-
Beliefs about a state of the world that can strongly influence the interpretation of new information. The concept is taken from Bayesian statistics, where incoming evidence is multiplied with a prior estimate to determine an event's posterior likelihood (which is the new prior before the next information arrives).
- Proximate mechanism
-
Biological mechanism that enables an organism to behave in the way it does. These mechanisms develop in response to the ultimate evolutionary causes for a given behaviour.
- Inequality aversion
-
Distaste for inequality in the distribution of outcomes. This concept — also referred to as inequity aversion — may motivate altruistic or fairness-related choices.
- Prisoner's dilemma game
-
An experimental paradigm to measure social cooperation. Two anonymous players decide whether to cooperate or to defect. For each individual player, unilateral cooperation yields the worst material payoff, whereas unilateral defection leads to the best material payoff. However, bilateral cooperation leads to a better payoff for each of the players than bilateral defection.
- Ultimatum game
-
An experimental paradigm to measure fairness preferences. Two anonymous players decide how to split a given sum of money. Player 1 can make an offer on how to split the money between the two players. Player 2 can accept or reject the offer. In case of acceptance, the decision will be implemented, but in case of rejection both players receive nothing. By rejecting positive but unfair offers, player 2 can punish player 1 at the cost of receiving nothing.
- Reverse inference
-
A scientific strategy of inferring the presence of a specific mental process when observing brain activity that has been correlated in previous studies with this process. This strategy can lead to invalid conclusions when used carelessly (because activity in a brain region may often be triggered by several different mental processes) and should be applied with caution.
- Repetition suppression
-
Phenomenon that repetition of the same stimulus elicits reduced activity in neurons specialized for this stimulus, possibly reflecting adaptation.
- Multivariate pattern analyses
-
Neuroimaging analyses that do not examine activity changes in each voxel in isolation but rather identify patterns of activity changes across spatially distributed voxels.
- Adaptive coding
-
Neural computations that are not fixed but adapt to the environment. For example, the same range of neural activity can encode different value ranges in different settings.
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Ruff, C., Fehr, E. The neurobiology of rewards and values in social decision making. Nat Rev Neurosci 15, 549–562 (2014). https://doi.org/10.1038/nrn3776
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DOI: https://doi.org/10.1038/nrn3776
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