Neural correlates of mentalizing-related computations during strategic interactions in humans

TLDR

Mentalizing an opponent’s state of mind is essential for successful competition, yet how this function is implemented in the brain remains poorly understood. The study aims to formulate a computational model of mentalizing capacity in strategic games. The authors used fMRI to scan participants playing a two‑player strategy game and correlated the computational model with brain activity. Model components mapped onto distinct mentalizing network regions: medial prefrontal cortex tracked expectations based on predicted influence, posterior superior temporal sulcus reflected influence‑update signals, indicating dissociable contributions to higher‑order strategizing.

Abstract

Competing successfully against an intelligent adversary requires the ability to mentalize an opponent's state of mind to anticipate his/her future behavior. Although much is known about what brain regions are activated during mentalizing, the question of how this function is implemented has received little attention to date. Here we formulated a computational model describing the capacity to mentalize in games. We scanned human subjects with functional MRI while they participated in a simple two-player strategy game and correlated our model against the functional MRI data. Different model components captured activity in distinct parts of the mentalizing network. While medial prefrontal cortex tracked an individual's expectations given the degree of model-predicted influence, posterior superior temporal sulcus was found to correspond to an influence update signal, capturing the difference between expected and actual influence exerted. These results suggest dissociable contributions of different parts of the mentalizing network to the computations underlying higher-order strategizing in humans.