Imaging models of valuation during social interaction in humans

The role of dopamine neurons in value-guided behavior has been described in computationally explicit terms. These developments have motivated new model-based probes of reward processing in healthy humans, and in recent years these same models have also been used to design and understand neural responses during simple social exchange. These latter applications have opened up the possibility of identifying new endophenotypes characteristic of biological substrates underlying psychiatric disease. In this report, we review model-based approaches to functional magnetic resonance imaging in healthy individuals and the application of these paradigms to psychiatric disorders. We show early results from the application of model-based human interaction at three disparate levels: 1) interaction with a single human, 2) interaction within small groups, and 3) interaction with signals generated by large groups. In each case, we show how reward-prediction circuitry is engaged by abstract elements of each paradigm with blood oxygen level-dependent imaging as a read-out; and, in the last case (i.e., signals generated by large groups) we report on direct electrochemical dopamine measurements during decision making in humans. Lastly, we discuss how computational approaches can be used to objectively assess and quantify elements of complex and hidden social decision-making processes.