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dc.contributor.authorSheikh, Usman Ayub
dc.contributor.authorCarreiras, Manuel
dc.contributor.authorSoto, David ORCID
dc.date.accessioned2021-03-02T14:12:34Z
dc.date.available2021-03-02T14:12:34Z
dc.date.issued2021
dc.identifier.citationUsman Ayub Sheikh, Manuel Carreiras, David Soto, Neurocognitive mechanisms supporting the generalization of concepts across languages, Neuropsychologia, Volume 153, 2021, 107740, ISSN 0028-3932, https://doi.org/10.1016/j.neuropsychologia.2020.107740es_ES
dc.identifier.issn0028-3932
dc.identifier.urihttp://hdl.handle.net/10810/50423
dc.descriptionAvailable online 31 December 2020.es_ES
dc.description.abstractThe neurocognitive mechanisms that support the generalization of semantic representations across different languages remain to be determined. Current psycholinguistic models propose that semantic representations are likely to overlap across languages, although there is evidence also to the contrary. Neuroimaging studies observed that brain activity patterns associated with the meaning of words may be similar across languages. However, the factors that mediate cross-language generalization of semantic representations are not known. We here identify a key factor: the depth of processing. Human participants were asked to process visual words as they underwent functional MRI. We found that, during shallow processing, multivariate pattern classifiers could decode the word semantic category within each language in putative substrates of the semantic network, but there was no evidence of cross-language generalization in the shallow processing context. By contrast, when the depth of processing was higher, significant cross-language generalization was observed in several regions, including inferior parietal, ventromedial, lateral temporal, and inferior frontal cortex. These results are in keeping with distributed-only views of semantic processing and favour models based on multiple semantic hubs. The results also have ramifications for existing psycholinguistic models of word processing such as the BIA+, which by default assumes non-selective access to both native and second languageses_ES
dc.description.sponsorshipD.S. acknowledges support from the Basque Government through the BERC 2018–2021 program, from the Spanish Ministry of Economy and Competitiveness, through the ’Severo Ochoa’ Programme for Centres/Units of Excellence in R&D (SEV-2015-490) and also from project grants PSI2016-76443-P from MINECO and PI-2017-25 from the Basque Government.es_ES
dc.language.isoenges_ES
dc.publisherNeuropsychologiaes_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/SEV-2015-0490es_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/PSI2016-76443-Pes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectSemantic representationes_ES
dc.subjectBilingualismes_ES
dc.subjectLanguagees_ES
dc.subjectMachine learninges_ES
dc.titleNeurocognitive mechanisms supporting the generalization of concepts across languageses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2021 Elsevier Ltd. All rights reserved.es_ES
dc.relation.publisherversionhttps://www.sciencedirect.com/journal/neuropsychologiaes_ES
dc.identifier.doi10.1016/j.neuropsychologia.2020.107740


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