dc.contributor.author | Wei, Yanjun | |
dc.contributor.author | Niu, Ying | |
dc.contributor.author | Taft, Marcus | |
dc.contributor.author | Carreiras, Manuel | |
dc.date.accessioned | 2023-11-28T09:42:33Z | |
dc.date.available | 2023-11-28T09:42:33Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Yanjun Wei, Ying Niu, Marcus Taft, Manuel Carreiras, Morphological decomposition in Chinese compound word recognition: Electrophysiological evidence, Brain and Language, Volume 241, 2023, 105267, ISSN 0093-934X, https://doi.org/10.1016/j.bandl.2023.105267 | es_ES |
dc.identifier.citation | Brain and Language | |
dc.identifier.issn | 0093-934X | |
dc.identifier.uri | http://hdl.handle.net/10810/63174 | |
dc.description | Available online 28 April 2023 | es_ES |
dc.description.abstract | The present study examined the effect of both morphological complexity and semantic transparency in Chinese compound word recognition. Using a visual lexical decision task, our electrophysiological results showed that transparent and opaque compounds induced stronger Left Anterior Negativity (LAN) than monomorphemic words. This result suggests that Chinese compounds might be decomposed into their constituent morphemes at the lemma level, whereas monomorphemic words are accessed as a whole-word lemma directly from the form level. In addition, transparent and opaque compounds produced a similar N400 as each other, suggesting that transparency did not show an effect on the involvement of constituent morphemes during access to the wholeword lemma. Two behavioral experiments additionally showed similar patterns to the EEG results. These findings support morphological decomposition for compounds at the lemma level as proposed by the full-parsing model, and no evidence is found to support the role of transparency during Chinese compound word recognition. | es_ES |
dc.description.sponsorship | This research was supported by the Science Foundation of Beijing Language and Culture University (the Fundamental Research Funds for the Central Universities) (19YJ130006, 21YJ190002); Humanities and Social Sciences Youth Foundation, Ministry of Education of the People’s Re- public of China (22YJC740082); Youth Talent Development Program at the Beijing Language and Culture University; China Scholarship Council. This research was also supported by the Basque Government through the BERC 2022-2025 program and by the Spanish State Research Agency through BCBL Severo Ochoa excellence accreditation CEX2020-001010-S. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | ELSEVIER | es_ES |
dc.relation | info:eu-repo/grantAgreement/GV/BERC2022-2025 | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/CEX2020-001010-S | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.subject | Chinese compound word | es_ES |
dc.subject | Morphological complexity | es_ES |
dc.subject | Morphological decomposition | es_ES |
dc.subject | Semantic transparency | es_ES |
dc.subject | EEG | es_ES |
dc.title | Morphological decomposition in Chinese compound word recognition: Electrophysiological evidence | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | © 2023 Elsevier Inc. All rights reserved. | es_ES |
dc.relation.publisherversion | https://www.sciencedirect.com/journal/brain-and-language | es_ES |
dc.identifier.doi | 10.1016/j.bandl.2023.105267 | |