Cho Jeonghwa, Brennan Jonathan R
Department of Linguistics, University of Michigan, United States; Department of English Language and Literature, Hongik University, South Korea.
Department of Linguistics, University of Michigan, United States.
Neuropsychologia. 2025 Jul 4;213:109150. doi: 10.1016/j.neuropsychologia.2025.109150. Epub 2025 Apr 23.
Diverse evidence supports the theory that bilingual language users have language-invariant representations of concepts and grammatical forms such as argument structure. Here we extend that work to test the representation of morphosyntactic features and lexical concepts in typologically different languages. Specifically, we deploy machine learning techniques with EEG data collected from eighteen Korean-English bilinguals while they read singular and plural nouns and present and past tense verbs in English and Korean. Whereas event-related potentials (ERPs) analyses show limited sensitivity to discriminate lexical, number, and tense information, neural decoding revealed robust within-language classification of lexical and morphosyntactic information in both languages. In contrast, between-languages decoding was possible only for number information; decoding of lexical items and tense did not generalize between the two languages, even when accounting for temporal differences. These results indicate stable within-language EEG representations for lexical items and morphosyntactic features but suggest that only the number feature show evidence for shared EEG response patterns between the two languages studied.
多种证据支持这样一种理论，即双语使用者对概念和语法形式（如论元结构）具有语言不变的表征。在此，我们扩展该研究工作，以测试类型学上不同语言中形态句法特征和词汇概念的表征。具体而言，我们运用机器学习技术，对18名韩英双语者在阅读英语和韩语的单数和复数名词以及现在时和过去时动词时收集的脑电图（EEG）数据进行分析。虽然事件相关电位（ERP）分析显示，区分词汇、数和时态信息的敏感性有限，但神经解码揭示了两种语言中词汇和形态句法信息在语言内部的稳健分类。相比之下，跨语言解码仅对数信息可行；即使考虑到时间差异，词汇项目和时态的解码也无法在两种语言之间推广。这些结果表明，词汇项目和形态句法特征在语言内部的脑电图表征是稳定的，但表明只有数特征显示出所研究的两种语言之间存在共享脑电图反应模式的证据。
