Inferring illness causes recruits the animacy semantic network

Abstract Inferring the causes of illness is universal across human cultures and is essential for survival. Here we use this phenomenon as a test case for understanding the neural basis of implicit causal inference. Participants (n=20) undergoing fMRI read two-sentence vignettes that encouraged them to make causal inferences about illness or mechanical failure (causal control) as well as non-causal vignettes. All vignettes were about people and were matched on linguistic variables. The same participants performed localizers: language, logical reasoning, and mentalizing. Inferring illness causes selectively engaged a portion of precuneus (PC) previously implicated in the semantic representation of animates (e.g., people, animals). This region was near but not the same as PC responses to mental states, suggesting a neural mind/body distinction. No cortical areas responded to causal inferences across domains (i.e., illness, mechanical), including in individually localized language and logical reasoning networks. Together, these findings suggest that implicit causal inferences are supported by content-specific semantic networks that encode causal knowledge.