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The Application of Computational Models to Social Neuroscience: Promises and Pitfalls

Charpentier, Caroline Juliette and O’Doherty, John P. (2018) The Application of Computational Models to Social Neuroscience: Promises and Pitfalls. Social Neuroscience, 13 (6). pp. 637-647. ISSN 1747-0919 . http://resolver.caltech.edu/CaltechAUTHORS:20180910-083324129

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Abstract

Interactions with conspecifics are key to any social species. In order to navigate this social world, it is crucial for individuals to learn from and about others. Whether it is learning a new skill by observing a parent perform it, avoiding negative outcomes, or making complex collective decisions, understanding the mechanisms underlying such social cognitive processes has been of considerable interest to psychologists and neuroscientists, particularly to studies of learning and decision-making. Here, we review studies that have used computational modelling techniques, combined with neuroimaging, to shed light on how people learn and make decisions in social contexts. As opposed to previous methods used in social neuroscience studies, the computational approach allows one to directly examine where in the brain particular computations, as estimated by models of behavior, are implemented. Similar to studies of experiential learning, findings suggest that learning from others can be implemented using several strategies: vicarious reward learning, where one learns from observing the reward outcomes of another agent; action imitation, which relies on encoding a prediction error between the expected and actual actions of the other agent; and social inference, where one learns by inferring the goals and intentions of others. These strategies rely on distinct neural networks, which may be recruited adaptively depending on task demands, the environment and other social factors.


Item Type:Article
Related URLs:
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https://doi.org/10.1080/17470919.2018.1518834DOIArticle
Additional Information:© 2018 Taylor & Francis. Received 18 Dec 2017, Accepted author version posted online: 01 Sep 2018, Published online: 12 Sep 2018. This work was supported by the National Institute of Mental Health [Caltech Conte Center for Social Decision Making].
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Subject Keywords:computational modeling, fMRI, social learning, social decision-making
Record Number:CaltechAUTHORS:20180910-083324129
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20180910-083324129
Official Citation:Caroline J. Charpentier & John P. O’Doherty (2018) The application of computational models to social neuroscience: promises and pitfalls, Social Neuroscience, 13:6, 637-647, DOI: 10.1080/17470919.2018.1518834
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:89473
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:10 Sep 2018 17:11
Last Modified:10 Oct 2018 17:39

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