发表机构
Dublin City University; VNUHCM – University of Science（都柏林城市大学; 越南国立大学胡志明市科学大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究利用脑电图探索大脑中单词可预测性的神经机制，重点关注N400时间窗口内不同词汇和语法类别情况。发现实词N400差异更明显，动词差异大于名词，名词可预测性信息更独特，且解码技术在捕捉认知过程表征上比传统分析更有效。
AI 中文摘要
人类发明了阅读并通过语言代代相传这一复杂技能。本研究为自下而上（与高阶语言结构相关）和自上而下（与下一个单词可预测性相关）过程背后的神经机制提供了实证证据，这两个过程在阅读时相互作用以引导理解。以往研究主要聚焦可预测性的N400效应或词汇类别，而关于可预测性如何影响不同词汇类别中N400反应的研究有限。在此，我们利用脑电图以毫秒分辨率记录大脑反应，重点研究不同词汇和语法类别在N400时间窗口（刺激后300 - 500毫秒）内可预测性对大脑反应的影响。结果表明，高和低完形概率水平之间N400反应的显著差异在实词上比虚词更明显。在两个主要实词类别中，动词的N400差异比名词更大，而名词比动词携带更多关于其可预测性的独特信息。此外，我们证明解码技术在捕捉随时间变化的认知过程的更详细和独特表征方面比传统的事件相关电位分析更有效。
英文摘要
Humans invented reading and have passed down this complex skill across generations through language. This study provides empirical evidence of the neural mechanisms underlying bottom-up (related to high-order linguistic structure) and top-down (related to next-word predictability) processes, which interact to guide comprehension during reading. While previous studies have focused on either the N400 effects of predictability or lexical categories, research on how predictability influences N400 responses across different lexical categories is limited, mainly due to constraints in publicly available datasets. Here, we examine how predictability influences brain responses, recorded at millisecond resolution using electroencephalography (EEG), with a focus on the N400 time window (300-500 ms post-stimulus) across different lexical and grammatical categories. Our results indicate that significant differences in N400 responses between high and low cloze probability levels were more pronounced for content words than function words. Among the two primary content categories, verbs exhibited greater N400 differences than nouns, while nouns carried more distinct information about their predictability than verbs. Moreover, we demonstrate that the decoding technique is more effective than the event-related potential (ERP) traditional analysis in capturing more detailed and distinct representations of cognitive processes over time.
