title: The computation of social behavior.
abstract: Neuroscientists are beginning to advance explanations of social behavior in terms of underlying brain mechanisms. Two distinct networks of brain regions have come to the fore. The first involves brain regions that are concerned with learning about reward and reinforcement. These same reward-related brain areas also mediate preferences that are social in nature even when no direct reward is expected. The second network focuses on regions active when a person must make estimates of another person's intentions. However, it has been difficult to determine the precise roles of individual brain regions within these networks or how activities in the two networks relate to one another. Some recent studies of reward-guided behavior have described brain activity in terms of formal mathematical models; these models can be extended to describe mechanisms that underlie complex social exchange. Such a mathematical formalism defines explicit mechanistic hypotheses about internal computations underlying regional brain activity, provides a framework in which to relate different types of activity and understand their contributions to behavior, and prescribes strategies for performing experiments under strong control.
authors.affiliation: Oxford Centre for Functional MRI of the Brain (FMRIB Centre), John Radcliffe Hospital, Oxford OX3 9DU, UK. behrens@fmrib.ox.ac.uk
authors.forename: Timothy E J
authors.initials: TE
authors.lastname: Behrens
authors.forename: Laurence T
authors.initials: LT
authors.lastname: Hunt
authors.forename: Matthew F S
authors.initials: MF
authors.lastname: Rushworth
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D003071:Cognition; D003657:Decision Making; D005544:Forecasting; D005717:Games, Experimental; D006179:Gyrus Cinguli / Q000502:physiology; D006801:Humans; D033182:Intention; D008960:Models, Psychological; D012054:Reinforcement, Psychology; D012201:Reward; D012919:Social Behavior