EEG decoding of spoken words in bilingual listeners: from words to language invariant semantic-conceptual representations.
EEG decoding of spoken words in bilingual listeners: from words to language invariant semantic-conceptual representations.
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DOI：
10.3389/fpsyg.2015.00071
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发表时间：
2015
影响因子：
3.8
通讯作者：
Bonte M
中科院分区：
文献类型：
--
作者：
Correia JM;Jansma B;Hausfeld L;Kikkert S;Bonte M
口语单词的识别和产生需要在声学、语音和概念神经表征之间快速转换。双语者在母语和非母语语言中进行这些转换，从等效但声学不同的单词中获得统一的语义概念。在这里，我们利用双语者的这种能力来研究大脑中的输入不变语义表征。我们获得了荷兰受试者的脑电图数据，他们精通英语，同时用两种语言听四个单音节和声学上不同的动物单词（例如，“paard”-“horse”）。多变量模式分析（Multivariate pattern analysis， MVPA）用于识别一种语言中单个单词的区别（语言内区别）和跨两种语言的泛化（跨语言泛化）的脑电反应模式。此外，采用两种脑电信号特征选择方法，我们评估了时间和振荡脑电信号特征对我们的分类结果的贡献。MVPA结果显示，在单词出现后较宽的时间窗（~ 50-620 ms）内，语言内辨别是可能的，这可能反映了单词之间的语音和语义概念差异。最有趣的是，在550-600毫秒之间可能出现显著的跨语言泛化，这表明激活了来自荷兰语和英语名词的共同语义-概念表征。这两种类型的分类都显示出低于12 Hz的振荡的强大贡献，表明低频振荡在单个单词和概念的神经表征中的重要性。本研究证明了MVPA从脑电图反应中解码单个口语单词并评估其语言不变语义-概念表征的光谱-时间动态的可行性。我们讨论了这种方法和结果如何与跟踪理解和产生概念编码的神经机制相关。
Spoken word recognition and production require fast transformations between acoustic, phonological, and conceptual neural representations. Bilinguals perform these transformations in native and non-native languages, deriving unified semantic concepts from equivalent, but acoustically different words. Here we exploit this capacity of bilinguals to investigate input invariant semantic representations in the brain. We acquired EEG data while Dutch subjects, highly proficient in English listened to four monosyllabic and acoustically distinct animal words in both languages (e.g., “paard”–“horse”). Multivariate pattern analysis (MVPA) was applied to identify EEG response patterns that discriminate between individual words within one language (within-language discrimination) and generalize meaning across two languages (across-language generalization). Furthermore, employing two EEG feature selection approaches, we assessed the contribution of temporal and oscillatory EEG features to our classification results. MVPA revealed that within-language discrimination was possible in a broad time-window (~50–620 ms) after word onset probably reflecting acoustic-phonetic and semantic-conceptual differences between the words. Most interestingly, significant across-language generalization was possible around 550–600 ms, suggesting the activation of common semantic-conceptual representations from the Dutch and English nouns. Both types of classification, showed a strong contribution of oscillations below 12 Hz, indicating the importance of low frequency oscillations in the neural representation of individual words and concepts. This study demonstrates the feasibility of MVPA to decode individual spoken words from EEG responses and to assess the spectro-temporal dynamics of their language invariant semantic-conceptual representations. We discuss how this method and results could be relevant to track the neural mechanisms underlying conceptual encoding in comprehension and production.
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