Electrophysiological insights into the processing of figurative two-part allegorical sayings

被引:16
作者
Zhang, Hui [1 ,2 ]
Jiang, Long [1 ]
Gu, Jiexin [2 ]
Yang, Yiming [2 ]
机构
[1] Nanjing Int Studies Univ, Res Ctr Linguist & Appl Linguist, Nanjing 210039, Jiangsu, Peoples R China
[2] Jiangsu Normal Univ, Jiangsu Key Lab Linguist Sci & Neurocognit, Inst Linguist, Xuzhou 221009, Peoples R China
基金
中国国家自然科学基金;
关键词
ERP; Figurative two-part allegorical sayings; N170; N380; Insight effect; BRAIN POTENTIALS; TIME-COURSE; FACES; N170; SENTENCES; LANGUAGE; DYNAMICS; METAPHOR;
D O I
10.1016/j.jneuroling.2013.01.004
中图分类号
H0 [语言学];
学科分类号
030303 ; 0501 ; 050102 ;
摘要
The paper employed ERP technique and Chinese traditional riddle-solving paradigm to explore the time courses and dynamic neural mechanisms of processing figurative two-part allegorical sayings. The results showed significant differences for two ERP components (N170 and N380) between highly familiar and highly unfamiliar linguistic stimuli: for both N170 and N380, highly familiar linguistic stimuli elicited significantly smaller ERP effects, whereas highly unfamiliar linguistic stimuli significantly larger. The N170 may be an ERP component which is related to an early recognition of perceptual discrepancy between the two parts of figurative two-part allegorical sayings, which can also be regarded as early preliminary context integration. The N380 is probably a significant index for the identification and solution of the semantic gap between the two parts. In the process, insight phenomenon was engendered when highly unfamiliar figurative two-part allegorical sayings were processed. What is worth mentioning is that the N170 and N380 have been reported for the first time in ERP studies in which Chinese idioms are chosen as linguistic stimuli. The paper has demonstrated empirically that it is the different activation relations between the first parts and the answers of the two different types of figurative two-part allegorical sayings that lead to the different time courses and dynamic neural mechanisms. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:421 / 439
页数:19
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