Neural correlates of emotion-label vs. emotion-laden word processing in late bilinguals : evidence from an ERP study
Tang, D., Li, X., Fu, Y., Wang, H., Li, X., Parviainen, T., & Kärkkäinen, T. (2024). Neural correlates of emotion-label vs. emotion-laden word processing in late bilinguals : evidence from an ERP study. Cognition and Emotion, Early online. https://doi.org/10.1080/02699931.2024.2352584
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Cognition and EmotionAuthors
Fu, Yang |
Date
2024Access restrictions
Embargoed until: 2025-05-14Request copy from author
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© 2024 Taylor & Francis
The brain processes underlying the distinction between emotion-label words (e.g. happy, sad) and emotion-laden words (e.g. successful, failed) remain inconclusive in bilingualism research. The present study aims to directly compare the processing of these two types of emotion words in both the first language (L1) and second language (L2) by recording event-related potentials (ERP) from late Chinese-English bilinguals during a lexical decision task. The results revealed that in the early word processing stages, the N170 emotion effect emerged only for L1 negative emotion-laden words and L2 negative emotion-label words. In addition, larger early posterior negativity (EPN) was elicited by emotion-laden words than emotion-label words in both L1 and L2. In the later processing stages, the N400 emotion effect was evident for L1 emotion words, excluding positive emotion-laden words, while it was absent in L2. Notably, L1 emotion words elicited enhanced N400 and attenuated late positive complex (LPC) compared to those in L2. Taken together, these findings confirmed the engagement of emotion, and highlighted the modulation of emotion word type and valence on word processing in both early and late processing stages. Different neural mechanisms between L1 and L2 in processing written emotion words were elucidated.
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https://converis.jyu.fi/converis/portal/detail/Publication/213665288
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Additional information about funding
This work was supported by the scholarship from China Scholar-ship Council [grant number 201906060171].License
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