谷歌浏览器插件
订阅小程序
在清言上使用

Hemispheric asymmetries in meaning selection: evidence from the disambiguation of homophonic vs. heterophonic homographs.

Brain and Cognition(2012)

引用 9|浏览1
暂无评分
摘要
Research investigating hemispheric asymmetries in meaning selection using homophonic homographs (e.g., bank), suggests that the left hemisphere (LH) quickly selects contextually relevant meanings, whereas the right hemisphere (RH) maintains a broader spectrum of meanings including those that are contextually irrelevant (e.g., Faust & Chiarello, 1998). The present study investigated cerebral asymmetries in maintaining the multiple meanings of two types of Hebrew homographs: homophonic homographs and heterophonic homographs (e.g., tear). Participants read homographs preceded by a biasing, or a non-biasing sentential context, and performed a lexical decision task on targets presented laterally, 1000ms after the onset of the sentence-final ambiguous prime. Targets were related to either the dominant or the subordinate meaning of the preceding homograph, or unrelated to it. When targets were presented in the LVF/RH, dominant and subordinate meanings, of both types of homographs, were retained only when they were supported by context. In a non-biasing context, only dominant meanings of homophonic homographs were retained. Alternatively, when targets were presented in the RVF/LH, priming effects for homophonic homographs were only evident when meanings were supported by both context and frequency (i.e., when context favored the dominant meaning). In contrast, heterophonic homographs resulted in activation of dominant meanings, in all contexts, and activation of subordinate meanings, only in subordinate-biasing contexts. The results challenge the view that a broader spectrum of meanings is maintained in the right than in the left hemisphere and suggest that hemispheric differences in the time course of meaning selection (or decay) may be modulated by phonology.
更多
查看译文
关键词
Ambiguity,Divided visual field,Cerebral asymmetry,Priming,Semantic processing,Homographs
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要