bioRxivNeurosciencePreprint
Expertise modifies neural responses to causal inference during language comprehension
Abstract
Linguistic communication relies on shared common ground, yet different individuals in a community have specialized semantic knowledge. As a key example, physicians acquire rich knowledge about the causes of illness. An open question is whether such "causal expertise" influences the neural basis of language comprehension. Here we tested the hypothesis that when understanding everyday language like, "Holly used a grimy faucet during her overseas plane ride. Now she has the stomach flu," medical experts retrieve richer representations in semantic networks of the brain. Physicians (n=16) and age- and education-matched controls (n=16) undergoing fMRI read two-sentence vignettes that elicited implicit causal inferences about illness or object mechanics as well as control vignettes that did not elicit causal inferences. Vignettes were linguistically matched across conditions and were accessible to experts and non-experts alike. Across both groups, causal vignettes about illness engaged a temporoparietal semantic network previously implicated in thinking about animates, i.e., people and animals (precuneus and left temporoparietal junction), whereas causal vignettes about object mechanics engaged a semantic network associated with places and objects. Critically, physicians' responses in the animacy network were more robust and self-similar, suggesting the activation of richer semantic knowledge. Medical expertise effects were specific to biological inferences rather than mechanical or mental state inferences. By contrast, individually localized frontotemporal language and frontoparietal reasoning networks did not respond preferentially to causally connected sentences or show effects of expertise. Our findings suggest that causal expertise alters neural responses to causal inferences that unfold automatically during language comprehension.
- organism: human
- assay: imaging
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Animacy semantic network supports implicit causal inferences about illness
Miriam Hauptman, Marina Bedny·bioRxiv·Jul 10, 2024
- Causal reasoning is domain-specific in the human brain
Raghavendrarao T Pramod, Jessica Chomik-Morales, … Nancy Kanwisher·bioRxiv·Oct 28, 2026
- Causal contributions of the domain-general (Multiple Demand) and the language-selective brain networks to perceptual and semantic challenges in speech comprehension
Lucy J. MacGregor, Rebecca Anne Gilbert, … Matthew H. Davis·Neurobiology of LanguagePeer-reviewed·Jan 1, 2022
- The Role of the Posterior Medial Network in Language Comprehension: Dissociating Construction of Episodic versus Semantic Representations
Francesca M. Branzi, Matthew A. Lambon Ralph·bioRxiv·Sep 3, 2022
- Incremental language comprehension difficulty predicts activity in the language network but not the multiple demand network
Leila Wehbe, Idan Blank, … Evelina G. Fedorenko·Cerebral CortexPeer-reviewed·Mar 2, 2021
- Evidence from Formal Logical Reasoning Reveals that the Language of Thought is not Natural Language
Hope Kean, Alexander Fung, … Evelina G. Fedorenko·Proceedings of the National Academy of SciencesPeer-reviewed·Jul 6, 2026