Slaats Sophie, Meyer Antje S, Martin Andrea E
Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands.
Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland.
Neurobiol Lang (Camb). 2024 Oct 11;5(4):942-980. doi: 10.1162/nol_a_00155. eCollection 2024.
When we understand language, we recognize words and combine them into sentences. In this article, we explore the hypothesis that listeners use probabilistic information about words to build syntactic structure. Recent work has shown that lexical probability and syntactic structure both modulate the delta-band (<4 Hz) neural signal. Here, we investigated whether the neural encoding of syntactic structure changes as a function of the distributional properties of a word. To this end, we analyzed MEG data of 24 native speakers of Dutch who listened to three fairytales with a total duration of 49 min. Using temporal response functions and a cumulative model-comparison approach, we evaluated the contributions of syntactic and distributional features to the variance in the delta-band neural signal. This revealed that lexical surprisal values (a distributional feature), as well as bottom-up node counts (a syntactic feature) positively contributed to the model of the delta-band neural signal. Subsequently, we compared responses to the syntactic feature between words with high- and low-surprisal values. This revealed a delay in the response to the syntactic feature as a consequence of the surprisal value of the word: high-surprisal values were associated with a delayed response to the syntactic feature by 150-190 ms. The delay was not affected by word duration, and did not have a lexical origin. These findings suggest that the brain uses probabilistic information to infer syntactic structure, and highlight an importance for the role of time in this process.
当我们理解语言时,我们识别单词并将它们组合成句子。在本文中,我们探讨了一个假设,即听众使用单词的概率信息来构建句法结构。最近的研究表明,词汇概率和句法结构都会调节δ波段(<4 Hz)神经信号。在这里,我们研究了句法结构的神经编码是否会随着单词的分布特性而变化。为此,我们分析了24名以荷兰语为母语的人的脑磁图(MEG)数据,这些人听了总时长为49分钟的三个童话故事。使用时间响应函数和累积模型比较方法,我们评估了句法和分布特征对δ波段神经信号方差的贡献。这表明词汇意外值(一种分布特征)以及自下而上的节点计数(一种句法特征)对δ波段神经信号模型有正向贡献。随后,我们比较了对具有高意外值和低意外值的单词的句法特征的反应。这揭示了由于单词的意外值,对句法特征的反应存在延迟:高意外值与对句法特征的反应延迟150 - 190毫秒相关。这种延迟不受单词时长的影响,也不是由词汇引起的。这些发现表明大脑使用概率信息来推断句法结构,并突出了时间在此过程中的重要作用。