Politics can seem home to the most calculating and yet least rational elements of humanity. How might we systematically characterize this spectrum of political cognition? Here, we propose reinforcement learning (RL) as a unified framework to dissect the political mind. RL describes how agents algorithmically navigate complex and uncertain domains like politics. Through this computational […]

Abstract The present study investigated whether humans are more likely to trust people who are coordinated with them. We examined a well-known type of linguistic coordination, lexical entrainment, typically involving the elaboration of “conceptual pacts,” or partner-specific agreements on how to conceptualize objects. In two experiments, we manipulated lexical entrainment in a referential communication task […]

IntroductionThe assessment of resting state (rs) neurophysiological dynamics relies on the control of sensory, perceptual, and behavioral environments to minimize variability and rule-out confounding sources of activation during testing conditions. Here, we investigated how temporally-distal environmental inputs, specifically metal exposures experienced up to several months prior to scanning, affect functional dynamics measured using rs functional […]