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Article: Delineating Region-Specific contributions and connectivity patterns for semantic association and categorization through ROI and Granger causality analysis

TitleDelineating Region-Specific contributions and connectivity patterns for semantic association and categorization through ROI and Granger causality analysis
Authors
KeywordsFmri
Functional connectivity
Granger causality
Semantic association
Semantic categorization
Taxonomic and thematic semantic relations
Issue Date1-Nov-2024
PublisherElsevier
Citation
Brain and Language, 2024, v. 258 How to Cite?
AbstractThe neural mechanisms supporting semantic association and categorization are examined in this study. Semantic association involves linking concepts through shared themes, events, or scenes, while semantic categorization organizes meanings hierarchically based on defining features. Twenty-three adults participated in an fMRI study performing categorization and association judgment tasks. Results showed stronger activation in the inferior frontal gyrus during association and marginally weaker activation in the posterior middle temporal gyrus (pMTG) during categorization. Granger causality analysis revealed bottom-up connectivity from the visual cortex to the hippocampus during semantic association, whereas semantic categorization exhibited strong reciprocal connections between the pMTG and frontal semantic control regions, together with information flow from the visual association area and hippocampus to the pars triangularis. We propose that demands on semantic retrieval, precision of semantic representation, perceptual experiences and world knowledge result in observable differences between these two semantic relations.
Persistent Identifierhttp://hdl.handle.net/10722/366308
ISSN
2023 Impact Factor: 2.1
2023 SCImago Journal Rankings: 0.881

 

DC FieldValueLanguage
dc.contributor.authorLiu, Chun Yin-
dc.contributor.authorQin, Lang-
dc.contributor.authorTao, Ran-
dc.contributor.authorDeng, Wenxiyuan-
dc.contributor.authorJiang, Tian-
dc.contributor.authorWang, Nizhuan-
dc.contributor.authorMatthews, Stephen-
dc.contributor.authorSiok, Wai Ting-
dc.date.accessioned2025-11-25T04:18:40Z-
dc.date.available2025-11-25T04:18:40Z-
dc.date.issued2024-11-01-
dc.identifier.citationBrain and Language, 2024, v. 258-
dc.identifier.issn0093-934X-
dc.identifier.urihttp://hdl.handle.net/10722/366308-
dc.description.abstractThe neural mechanisms supporting semantic association and categorization are examined in this study. Semantic association involves linking concepts through shared themes, events, or scenes, while semantic categorization organizes meanings hierarchically based on defining features. Twenty-three adults participated in an fMRI study performing categorization and association judgment tasks. Results showed stronger activation in the inferior frontal gyrus during association and marginally weaker activation in the posterior middle temporal gyrus (pMTG) during categorization. Granger causality analysis revealed bottom-up connectivity from the visual cortex to the hippocampus during semantic association, whereas semantic categorization exhibited strong reciprocal connections between the pMTG and frontal semantic control regions, together with information flow from the visual association area and hippocampus to the pars triangularis. We propose that demands on semantic retrieval, precision of semantic representation, perceptual experiences and world knowledge result in observable differences between these two semantic relations.-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofBrain and Language-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectFmri-
dc.subjectFunctional connectivity-
dc.subjectGranger causality-
dc.subjectSemantic association-
dc.subjectSemantic categorization-
dc.subjectTaxonomic and thematic semantic relations-
dc.titleDelineating Region-Specific contributions and connectivity patterns for semantic association and categorization through ROI and Granger causality analysis-
dc.typeArticle-
dc.identifier.doi10.1016/j.bandl.2024.105476-
dc.identifier.scopuseid_2-s2.0-85205225977-
dc.identifier.volume258-
dc.identifier.eissn1090-2155-
dc.identifier.issnl0093-934X-

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