title: Insights from the application of computational neuroimaging to social neuroscience.
abstract: A recent approach in social neuroscience has been the application of formal computational models for a particular social-cognitive process to neuroimaging data. Here we review preliminary findings from this nascent subfield, focusing on observational learning and strategic interactions. We present evidence consistent with the existence of three distinct learning systems that may contribute to social cognition: an observational-reward-learning system involved in updating expectations of future reward based on observing rewards obtained by others, an action-observational learning system involved in learning about the action tendencies of others, and a third system engaged when it is necessary to learn about the hidden mental-states or traits of another. These three systems appear to map onto distinct neuroanatomical substrates, and depend on unique computational signals.
authors.affiliation: California Institute of Technology, Pasadena, CA 91125, USA.
authors.forename: Simon
authors.initials: S
authors.lastname: Dunne
authors.forename: John P
authors.initials: JP
authors.lastname: O'Doherty
mesh_terms: D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D007858:Learning / Q000502:physiology*; D059906:Neuroimaging; D009488:Neurosciences / Q000639:trends*; D012201:Reward; D012919:Social Behavior