Data-driven computational models reveal perceptual simulation in word processing

In their strongest formulation, theories of grounded cognition claim that concepts are made up sensorimotor information. Following such equivalence, perceptual properties objects should consistently influence processing, even in purely linguistic tasks, where information is neither solicited nor required. Previous studies have tested this prediction semantic priming but they not observed influences on participants’ performances. However, those findings suffer from critical shortcomings, which may prevented potential visually grounded/perceptual effects being detected. Here, we investigate topic by applying an innovative method expected to increase the sensitivity detecting effects. Specifically, adopt objective, data-driven, computational approach independently quantify vision-based and language-based similarities for prime-target pairs a continuous scale. We test whether these measures predict behavioural performance mega-study with various experimental settings. Vision-based similarity found facilitate performance, dissociation between was also observed. Thus, line cognition, can word processing at same time challenges strong claims conceptual equivalence.