Breaking human social decision making into multiple components and then putting them together again

Most of our waking time as human beings is spent interacting with other individuals. In order to make good decisions in this social milieu, it is often necessary to make inferences about the internal states, traits and intentions of others. Recently, some progress has been made to uncover the neural computations underlying human social decision-making by combining functional magnetic resonance neuroimaging (fMRI) with computational modeling of behavior. Modeling of behavioral data allows us to identify key computations necessary for decision-making and how these computations are integrated. Furthermore, by correlating these computational variables against neuroimaging data, it has become possible to elucidate where in the brain various computational variables are implemented during social decision making. Here we review the current state of knowledge in the domain of social computational neuroscience. Findings to date have emphasized that social decisions are driven by multiple computations that are conducted in parallel and which are implemented in distinct brain regions. We suggest that further progress is going to depend on identifying how and where such variables get integrated in order to yield a coherent behavioral output