The evolution of human social cognitive capacities such as mentalizing was associated with the expansion of frontoparietal cortical networks, particularly the default network. Mentalizing supports prosocial behaviors, but recent evidence indicates it may also serve a darker side of human social behavior. Using a computational reinforcement learning model of decision-making on a social exchange task, we examined how individuals optimized their approach to social interactions based on a counterpart's behavior and prior reputation. We found that learning signals encoded in the default network scaled with reciprocal cooperation and were stronger in individuals who were more exploitative and manipulative, but weaker in those who were more callous and less empathic. These learning signals, which help to update predictions about others' behavior, accounted for associations between exploitativeness, callousness, and social reciprocity. Separately, we found that callousness, but not exploitativeness, was associated with a behavioral insensitivity to prior reputation effects. While the entire default network was involved in reciprocal cooperation, sensitivity to reputation was selectively related to the activity of the medial temporal subsystem. Overall, our findings suggest that the emergence of social cognitive capacities associated with the expansion of the default network likely enabled humans to not only cooperate effectively with others, but to exploit and manipulate others as well.
Keywords: default network; individual differences; mentalizing; reciprocal cooperation; social learning.