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

Petilli, M., Günther, F., Vergallito, A., Ciapparelli, M., Marelli, M. (2021). Data-driven computational models reveal perceptual simulation in word processing. JOURNAL OF MEMORY AND LANGUAGE, 117 [10.1016/j.jml.2020.104194].

Data-driven computational models reveal perceptual simulation in word processing

Petilli, MA
;
Vergallito, A;Ciapparelli, M;Marelli, M
2021

Abstract

In their strongest formulation, theories of grounded cognition claim that concepts are made up of sensorimotor information. Following such equivalence, perceptual properties of objects should consistently influence processing, even in purely linguistic tasks, where perceptual information is neither solicited nor required. Previous studies have tested this prediction in semantic priming tasks, but they have not observed perceptual influences on participants’ performances. However, those findings suffer from critical shortcomings, which may have prevented potential visually grounded/perceptual effects from being detected. Here, we investigate this topic by applying an innovative method expected to increase the sensitivity in detecting such perceptual effects. Specifically, we adopt an objective, data-driven, computational approach to independently quantify vision-based and language-based similarities for prime-target pairs on a continuous scale. We test whether these measures predict behavioural performance in a semantic priming mega-study with various experimental settings. Vision-based similarity is found to facilitate performance, but a dissociation between vision-based and language-based effects was also observed. Thus, in line with theories of grounded cognition, perceptual properties can facilitate word processing even in purely linguistic tasks, but the behavioural dissociation at the same time challenges strong claims of sensorimotor and conceptual equivalence.
Articolo in rivista - Articolo scientifico
Convolutional neural networks; Distributional semantic models; Grounded cognition; Perceptual simulation; Semantic priming;
English
Petilli, M., Günther, F., Vergallito, A., Ciapparelli, M., Marelli, M. (2021). Data-driven computational models reveal perceptual simulation in word processing. JOURNAL OF MEMORY AND LANGUAGE, 117 [10.1016/j.jml.2020.104194].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/349177
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