Cibelli Emily S, Leonard Matthew K, Johnson Keith, Chang Edward F
Department of Linguistics, University of California, Berkeley, 1203 Dwinelle Hall, Berkeley, CA 94720, USA.
Department of Neurological Surgery, University of California, San Francisco, 505 Parnassus Avenue, San Francisco, CA 94143, USA.
Brain Lang. 2015 Aug;147:66-75. doi: 10.1016/j.bandl.2015.05.005. Epub 2015 Jun 11.
Neural representations of words are thought to have a complex spatio-temporal cortical basis. It has been suggested that spoken word recognition is not a process of feed-forward computations from phonetic to lexical forms, but rather involves the online integration of bottom-up input with stored lexical knowledge. Using direct neural recordings from the temporal lobe, we examined cortical responses to words and pseudowords. We found that neural populations were not only sensitive to lexical status (real vs. pseudo), but also to cohort size (number of words matching the phonetic input at each time point) and cohort frequency (lexical frequency of those words). These lexical variables modulated neural activity from the posterior to anterior temporal lobe, and also dynamically as the stimuli unfolded on a millisecond time scale. Our findings indicate that word recognition is not purely modular, but relies on rapid and online integration of multiple sources of lexical knowledge.
单词的神经表征被认为具有复杂的时空皮层基础。有人提出,口语单词识别并非是从语音形式到词汇形式的前馈计算过程,而是涉及自下而上的输入与存储的词汇知识的在线整合。通过对颞叶进行直接神经记录,我们研究了皮层对单词和伪词的反应。我们发现,神经群体不仅对词汇状态(真实词与伪词)敏感,而且对词群大小(每个时间点与语音输入匹配的单词数量)和词群频率(这些单词的词汇频率)也敏感。这些词汇变量从前颞叶到后颞叶调节神经活动,并且在刺激以毫秒时间尺度展开时也动态调节。我们的研究结果表明,单词识别并非纯粹模块化,而是依赖于多种词汇知识来源的快速在线整合。