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理解汉语中的时间关系:一项事件相关电位研究

Understanding Temporal Relations in Mandarin Chinese: An ERP Investigation.

作者信息

Chen Lijuan, Lu Yiyi, Xu Xiaodong

机构信息

School of Foreign Studies, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.

School of Foreign Languages and Cultures, Nanjing Normal University, Nanjing 210097, China.

出版信息

Brain Sci. 2022 Apr 3;12(4):474. doi: 10.3390/brainsci12040474.

Abstract

Temporal connectives play a crucial role in marking the sequence of events during language comprehension. Although existing studies have shown that sentence comprehension can be modulated by temporal connectives, they have mainly focused on languages with grammatical tense such as English. It thus remains unclear how temporal information is processed in tenseless languages. The present study used event-related potentials (ERPs) to examine how world knowledge is retrieved and integrated in sentences linked by (before) and (after) in Mandarin Chinese (e.g., ). The critical words (e.g., fresh) were either congruent or incongruent with world knowledge. Relative to the -congruent sentences, the -incongruent sentences evoked a P600 on critical words and a negativity on sentence-final words, whereas relative to -congruent sentences, -incongruent sentences showed no significant difference on critical words but a sustained negativity on sentence-final words. Additionally, -congruent sentences elicited a larger sustained positivity (P600) than -congruent sentences. The results suggest that is more difficult to process than in Mandarin Chinese, supporting the iconicity account of temporal relations.

摘要

时间连接词在语言理解过程中标记事件顺序方面起着至关重要的作用。尽管现有研究表明句子理解会受到时间连接词的调节,但这些研究主要集中在具有语法时态的语言,如英语。因此,目前尚不清楚在没有时态的语言中时间信息是如何被处理的。本研究使用事件相关电位(ERP)来考察在汉语中由“在……之前”(before)和“在……之后”(after)连接的句子中,世界知识是如何被提取和整合的(例如,……)。关键单词(如“新鲜的”)与世界知识要么一致,要么不一致。相对于“在……之前”一致的句子,“在……之前”不一致的句子在关键单词上诱发了一个P600,并在句末单词上诱发了一个负波,而相对于“在……之后”一致的句子,“在……之后”不一致的句子在关键单词上没有显著差异,但在句末单词上有持续的负波。此外,“在……之后”一致的句子比“在……之前”一致的句子诱发了更大的持续正波(P600)。结果表明,在汉语中“在……之前”比“在……之后”更难处理,这支持了时间关系的象似性解释。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c09/9033067/156d724b7654/brainsci-12-00474-g001.jpg

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