Computational Models in Social Neuroscience
Jin Hyun Cheong, Eshin Jolly, Sunhae Sul, Luke J. Chang
Abstract
Jin Hyun Cheong, Eshin Jolly, Sunhae Sul, Luke J. Chang
Abstract
A growing trend in social neuroscience is the use of computational models to describe the psychological and neural processes underlying social cognition and behavior. Borrowing frameworks from expected utility theory, reinforcement learning, and game theory, this technique of formalizing psychological concepts has provided insights into how complex psychological computations such as social learning and mentalizing are processed in the brain. In this article, we highlight these findings and provide suggestions, while advocating greater use of computational methods in social neuroscience research.
OpenAlex reports 25 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
A growing trend in social neuroscience is the use of computational models to describe the psychological and neural processes underlying social cognition and behavior. Borrowing frameworks from expected utility theory, reinforcement learning, and game theory, this technique of formalizing psychological concepts has provided insights into how complex psychological computations such as social learning and mentalizing are processed in the brain. In this article, we highlight these findings and provide suggestions, while advocating greater use of computational methods in social neuroscience research.
Key concepts: Social neuroscience, Computational neuroscience, Developmental cognitive neuroscience, Cognitive neuroscience, Cognitive science, Social cognition, Social decision making, Neuroeconomics