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The Neural Correlates of the Interaction between Semantic and Phonological Processing for Chinese Character Reading

机译:汉字阅读的语义与语音处理相互作用的神经相关

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Visual word recognition involves mappings among orthographic, phonological, and semantic codes. In alphabetic languages, it is hard to disentangle the effects of these codes, because orthographically well-formed words are typically pronounceable, confounding orthographic and phonological processes, and orthographic cues to meaning are rare, and where they occur are morphological, confounding orthographic and semantic processes. In Chinese character recognition, it is possible to explore orthography to phonology (O-P) and orthography to semantics (O-S) processes independently by taking advantage of the distinct phonetic and semantic components in Chinese phonograms. We analyzed data from an fMRI experiment using lexical decision for Chinese characters to explore the sensitivity of areas associated with character recognition to orthographic, phonological, and semantic processing. First, a correlation approach was used to identify regions associated with reaction time, frequency, consistency and visual complexity. Then, these ROIs were examined for their responses to stimuli with different types of information available. These results revealed two neural pathways, one for O-S processing relying on left middle temporal gyrus and angular gyrus, and the other for O-P processing relying on inferior frontal gyrus and insula. The two neural routes form a shared neural network both for real and pseudo-characters, and their cooperative division of labor reflects the neural basis for processing different types of characters. Results are broadly consistent with findings from alphabetic languages, as predicted by reading models that assume the same general architecture for logographic and alphabetic scripts.
机译:视觉单词识别涉及拼字,语音和语义代码之间的映射。在字母语言中,很难解开这些代码的作用,因为拼写正确的单词通常发音清晰,拼写和语音过程令人困惑,拼写提示的含义很少见,出现的地方是词法,拼写拼写和语义流程。在汉字识别中,可以利用汉字中不同的语音和语义成分,分别探索从拼字法到音韵(O-P)和从拼字法到语义(O-S)的过程。我们分析了来自fMRI实验的数据,其中使用了针对汉字的词汇决策,以探索与字符识别相关的区域对正交,语音和语义处理的敏感性。首先,使用相关方法来识别与反应时间,频率,一致性和视觉复杂性相关的区域。然后,使用不同类型的可用信息检查这些ROI对刺激的反应。这些结果揭示了两种神经途径,一种途径是依赖于左颞中回和角状回的O-S处理,另一种依赖于额下回和绝缘的O-P处理。两条神经路径形成了针对实字符和伪字符的共享神经网络,它们的合作分工反映了处理不同类型字符的神经基础。结果大致与字母语言的发现一致,这是通过阅读模型所预测的,这些模型假定对逻辑文字和字母脚本具有相同的通用体系结构。

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