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      Neurocomputational mechanisms of prosocial learning and links to empathy

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          Abstract

          Reinforcement learning theory powerfully characterizes how we learn to benefit ourselves. In this theory, prediction errors-the difference between a predicted and actual outcome of a choice-drive learning. However, we do not operate in a social vacuum. To behave prosocially we must learn the consequences of our actions for other people. Empathy, the ability to vicariously experience and understand the affect of others, is hypothesized to be a critical facilitator of prosocial behaviors, but the link between empathy and prosocial behavior is still unclear. During functional magnetic resonance imaging (fMRI) participants chose between different stimuli that were probabilistically associated with rewards for themselves (self), another person (prosocial), or no one (control). Using computational modeling, we show that people can learn to obtain rewards for others but do so more slowly than when learning to obtain rewards for themselves. fMRI revealed that activity in a posterior portion of the subgenual anterior cingulate cortex/basal forebrain (sgACC) drives learning only when we are acting in a prosocial context and signals a prosocial prediction error conforming to classical principles of reinforcement learning theory. However, there is also substantial variability in the neural and behavioral efficiency of prosocial learning, which is predicted by trait empathy. More empathic people learn more quickly when benefitting others, and their sgACC response is the most selective for prosocial learning. We thus reveal a computational mechanism driving prosocial learning in humans. This framework could provide insights into atypical prosocial behavior in those with disorders of social cognition.

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          Most cited references52

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          The functional architecture of human empathy.

          Empathy accounts for the naturally occurring subjective experience of similarity between the feelings expressed by self and others without loosing sight of whose feelings belong to whom. Empathy involves not only the affective experience of the other person's actual or inferred emotional state but also some minimal recognition and understanding of another's emotional state. In light of multiple levels of analysis ranging from developmental psychology, social psychology, cognitive neuroscience, and clinical neuropsychology, this article proposes a model of empathy that involves parallel and distributed processing in a number of dissociable computational mechanisms. Shared neural representations, self-awareness, mental flexibility, and emotion regulation constitute the basic macrocomponents of empathy, which are underpinned by specific neural systems. This functional model may be used to make specific predictions about the various empathy deficits that can be encountered in different forms of social and neurological disorders.
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            Bayes Factors

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              The social neuroscience of empathy.

              The phenomenon of empathy entails the ability to share the affective experiences of others. In recent years social neuroscience made considerable progress in revealing the mechanisms that enable a person to feel what another is feeling. The present review provides an in-depth and critical discussion of these findings. Consistent evidence shows that sharing the emotions of others is associated with activation in neural structures that are also active during the first-hand experience of that emotion. Part of the neural activation shared between self- and other-related experiences seems to be rather automatically activated. However, recent studies also show that empathy is a highly flexible phenomenon, and that vicarious responses are malleable with respect to a number of factors--such as contextual appraisal, the interpersonal relationship between empathizer and other, or the perspective adopted during observation of the other. Future investigations are needed to provide more detailed insights into these factors and their neural underpinnings. Questions such as whether individual differences in empathy can be explained by stable personality traits, whether we can train ourselves to be more empathic, and how empathy relates to prosocial behavior are of utmost relevance for both science and society.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proc Natl Acad Sci USA
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                August 30 2016
                August 30 2016
                August 30 2016
                August 15 2016
                : 113
                : 35
                : 9763-9768
                Article
                10.1073/pnas.1603198113
                5024617
                27528669
                ee6b6199-f4d8-47e5-ae7f-bf724804d930
                © 2016

                Free to read

                http://www.pnas.org/site/misc/userlicense.xhtml

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