The neurobiology of rewards and values in social decision making

Journal name:
Nature Reviews Neuroscience
Volume:
15,
Pages:
549–562
Year published:
DOI:
doi:10.1038/nrn3776
Published online

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.

At a glance

Figures

  1. Two schemas for neural value computation in social versus non-social contexts.
    Figure 1: Two schemas for neural value computation in social versus non-social contexts.

    The figure illustrates two competing schemas for how the brain may determine the value of social and non-social factors during decision making. Please note that this illustration does not show specific brain areas and connections but rather depicts abstract principles of how brain areas and their interactions could implement these computations. a | The 'extended common currency schema' assumes that a single neural circuit (shown in purple) determines the motivational significance of both social and non-social events. The activity of this circuit represents the integrated value of all factors that are relevant for a choice; however, the perceptual and cognitive information that is relevant for these unified value computations may differ between social and non-social choices and may be provided by distinct domain-specific brain areas (shown in blue and red, respectively). Social and non-social decisions should thus result in identical activity in reward-related brain areas (if their motivational and hedonic properties are matched) but may differ in the functional connectivity of these shared valuation areas with other brain regions. b | The 'social-valuation-specific schema' is based on the social brain hypothesis, which proposes that social aspects of the environment are processed in a neural circuitry that evolved specifically to deal with these demands. In this schema, neural valuation of social and non-social factors engages neural processes that follow similar computational principles but are implemented in distinct neuronal populations that are specialized for each type of information. These specialized neurons may be located in different areas (shown in light blue and light red, respectively) or in close proximity within a value-processing brain region. In either case, the two types of valuation neurons (social versus non-social) will predominantly show functional interactions with other areas that are specialized for either social or non-social cognitive functions, respectively.

  2. Social influences on brain activity during reward processing.
    Figure 2: Social influences on brain activity during reward processing.

    a | 'Social' outcomes (emotional faces) and 'monetary' outcomes (financial wins and losses) in a value-learning task elicit similar activation in both the ventromedial prefrontal cortex (vmPFC; circled in blue) and the ventral striatum (circled in orange). Specifically, the two types of task induce similar subjective value (SV) signals during choices as well as reward (R) and prediction-error (PE) signals during outcomes. b | Oxytocin blocks learning-related activity changes in the amygdala during decisions related to trust. Feedback about breaches of trust lead to decreases in trust and trust-correlated blood-oxygen-level-dependent (BOLD) signal increases in placebo–treated individuals but not in oxytocin-treated individuals. c | Decision-value coding in the vmPFC flexibly adapts to different social frames of reference. When participants make choices for themselves ('self-choice'), then vmPFC BOLD signals reflect the decision values of the relevant options ('self-value'). By contrast, when choices are made for another person ('other choice'), vmPFC BOLD signals reflect the decision values of the options for this person ('other value'). d | The BOLD signal in the vmPFC reflects a vicarious prediction error during observation of another person's choices. The plot shows the time course of BOLD activity evoked by observing the other's outcome (time 0) when the outcome was better (blue) or worse (red) than expected. Part a is adapted with permission from Ref. 22, Oxford University Press. Part b is adapted with permission from Ref. 49, Cell Press/Elsevier. Part c is adapted with permission from Ref. 70, Cell Press/Elsevier. Part d is adapted with permission from Ref. 74, National Academy of Sciences.

  3. Social influences on brain activity during choice behaviour and learning.
    Figure 3: Social influences on brain activity during choice behaviour and learning.

    a | Inequality modulates value-related blood-oxygen-level-dependent (BOLD) signals in the ventromedial prefrontal cortex (vmPFC) and striatum. Participants were randomly given a higher endowment (high-pay group) or lower endowment (low-pay group) than an interaction partner. Identical monetary transfers from the experimenter to both players led to different neural responses, with higher BOLD activity for transfers to the player who had less starting capital. b | Social value orientation is associated with BOLD activation in the amygdala in response to unequal financial payoffs to self and other. Participants with a prosocial value orientation show increased amygdala activity for large differences between payoffs to themselves or the other, whereas participants with an individualistic value orientation show the opposite. Each bar represents the strength of this relation for one participant. c | The risk associated with non-monetary social decisions (that is, the probability in a fictitious moral dilemma that humans will die as a consequence of the participant's choice) elicits BOLD activity in the anterior insula; this neural measure predicted how strongly participants adapted their choices to avoid this risk. d | BOLD signals in the ventral striatum during face attractiveness ratings change if the ratings of other people disagree, indicating influences of social conformity on ventral striatum responses. Faces originally matched in attractiveness elicit higher (or lower) ratings and ventral striatum BOLD activity after feedback that peers rate these faces as higher (or lower) than oneself. Part a is from Ref. 80, Nature Publishing Group. Part b is from Ref. 81, Nature Publishing Group. Part c is adapted with permission from Ref. 98, Cell Press/Elsevier. Part d is adapted with permission from Ref. 102, © 2011 by SAGE Publications.

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Affiliations

  1. Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich, Bluemlisalpstrasse 10, CH-8006 Zurich, Switzerland.

    • Christian C. Ruff &
    • Ernst Fehr

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The authors declare no competing interests.

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  • Christian C. Ruff

    Christian C. Ruff is Professor of Neuroeconomics and Decision Neuroscience and a principal investigator at the Laboratory for Social and Neural Systems Research at the University of Zurich, Switzerland. He completed his Ph.D. and postdoctoral training with Jon Driver at the Institute for Cognitive Neuroscience and the Wellcome Trust Centre for Neuroimaging at University College London, UK. His research group uses combinations of neurostimulation and neuroimaging techniques to study the neural mechanisms underlying human decision making. Christian C. Ruff's homepage.

  • Ernst Fehr

    Ernst Fehr is Professor of Microeconomics and Experimental Economics, Chairman of the Department of Economics, and Director of the UBS International Center of Economics in Society at the University of Zurich, Switzerland. He completed his doctoral thesis at the University of Vienna, Austria, in 1986. He studies how society — through its economic institutions and social norms — shapes human preferences and the underlying neural circuitry. Ernst Fehr's homepage.

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