- Princeton Neuroscience Institute
- Computational Neuroscience
My research is concentrated on understanding the neural substrates of social cognition. The most complicated interactions we perform in our environment are those with other human beings: we must infer their intentions, anticipate their actions, and know what responses our actions are likely to induce. The complexity of even the most basic interpersonal interaction requires the use of sophisticated neural circuitry devoted to navigating our social world.
By using simplified multi-person tasks, I can provide a quantitative framework for analyzing and modeling social interactions. These tasks are often in the form of economic games, where subjects participate in the context of a small group while trying to maximize the reward that they earn. Since I can control the amount of information passing between subjects, I can determine what types of actions affect a subject’s behavior, and how a subject is likely to respond when these events occur. By utilizing Hyperscanning (simultaneous acquisition of fMRI data from multiple subjects), I can also ascertain what neural computations constitute the processing of social information.
The purpose of this research is to turn what has previously been a highly qualitative area of study (the psychology of interpersonal interactions) into a quantitative set of theories upon which mathematical models of social cognition in the human brain can be built and tested.