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Updated: Nov 24, 2025

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Published on: May 31, 2018
Concurrent use of animacy and event-knowledge during comprehension: Evidence from event-related potentials
Mariana Vega-Mendoza1, Martin J Pickering2, Mante S Nieuwland3
1Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, Scotland, UK; Department of Business Administration, Technology and Social Sciences. Engineering Psychology, Luleå University of Technology, Luleå, Sweden.
Abstract:
In two ERP experiments, we investigated whether readers prioritize animacy over real-world event-knowledge during sentence comprehension. We used the paradigm of Paczynski and Kuperberg (2012), who argued that animacy is prioritized based on the observations that the 'related anomaly effect' (reduced N400s for context-related anomalous words compared to unrelated words) does not occur for animacy violations, and that animacy violations but not relatedness violations elicit P600 effects. Participants read passive sentences with plausible agents (e.g., The prescription for the mental disorder was written by the psychiatrist) or implausible agents that varied in animacy and semantic relatedness (schizophrenic/guard/pill/fence). In Experiment 1 (with a plausibility judgment task), plausible sentences elicited smaller N400s relative to all types of implausible sentences. Crucially, animate words elicited smaller N400s than inanimate words, and related words elicited smaller N400s than unrelated words, but Bayesian analysis revealed substantial evidence against an interaction between animacy and relatedness. Moreover, at the P600 time-window, we observed more positive ERPs for animate than inanimate words and for related than unrelated words at anterior regions. In Experiment 2 (without judgment task), we observed an N400 effect with animacy violations, but no other effects. Taken together, the results of our experiments fail to support a prioritized role of animacy information over real-world event-knowledge, but they support an interactive, constraint-based view on incremental semantic processing.

