Beyond what was said: Neural computations underlying pragmatic reasoning in referential communication

Abstract

The ability to infer a speaker's utterance within a particular context for the intended meaning is central to communication. Yet, little is known about the underlying neurocomputational mechanisms of pragmatic inference, let alone relevant differences among individuals. Here, using a reference game combined with model-based functional magnetic resonance imaging (fMRI), we showed that an individual-level pragmatic inference model was a better predictor of listeners’ performance than a population-level model. Our fMRI results showed that Bayesian posterior probability was positively correlated with activity in the ventromedial prefrontal cortex (vmPFC) and ventral striatum and negatively correlated with activity in dorsomedial PFC, anterior insula (AI), and inferior frontal gyrus (IFG). Importantly, individual differences in higher-order reasoning were correlated with stronger activation in IFG and AI and positively modulated the vmPFC functional connectivity with AI. Our findings provide a preliminary neurocomputational account of how the brain represents Bayesian belief inferences and the neural basis of heterogeneity in such reasoning.