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The time course of cross-modal representations of conceptual categories

Authors :
Julien Dirani
Liina Pylkkänen
Source :
NeuroImage, Vol 277, Iss , Pp 120254- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

To what extent does language production activate cross-modal conceptual representations? In picture naming, we view specific exemplars of concepts and then name them with a label, like “dog”. In overt reading, the written word does not express a specific exemplar. Here we used a decoding approach with magnetoencephalography (MEG) to address whether picture naming and overt word reading involve shared representations of superordinate categories (e.g., animal). This addresses a fundamental question about the modality-generality of conceptual representations and their temporal evolution. Crucially, we do this using a language production task that does not require explicit categorization judgment and that controls for word form properties across semantic categories. We trained our models to classify the animal/tool distinction using MEG data of one modality at each time point and then tested the generalization of those models on the other modality. We obtained evidence for the automatic activation of cross-modal semantic category representations for both pictures and words later than their respective modality-specific representations. Cross-modal representations were activated at 150 ms and lasted until around 450 ms. The time course of lexical activation was also assessed revealing that semantic category is represented before lexical access for pictures but after lexical access for words. Notably, this earlier activation of semantic category in pictures occurred simultaneously with visual representations. We thus show evidence for the spontaneous activation of cross-modal semantic categories in picture naming and word reading. These results serve to anchor a more comprehensive spatio-temporal delineation of the semantic feature space during production planning.

Details

Language :
English
ISSN :
10959572
Volume :
277
Issue :
120254-
Database :
Directory of Open Access Journals
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
edsdoj.1db0cd86ef2240a4baf4c9f50629165c
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neuroimage.2023.120254