Division of Psychology, School of Humanities and Social Sciences, Nanyang Technological University, Singapore.
Neuroimage. 2012 Oct 15;63(1):381-91. doi: 10.1016/j.neuroimage.2012.06.047. Epub 2012 Jul 1.
A growing body of neuroimaging evidence has shown that Chinese character processing recruits differential activation from alphabetic languages due to its unique linguistic features. As more investigations on Chinese character processing have recently become available, we applied a meta-analytic approach to summarize previous findings and examined the neural networks for orthographic, phonological, and semantic processing of Chinese characters independently. The activation likelihood estimation (ALE) method was used to analyze eight studies in the orthographic task category, eleven in the phonological and fifteen in the semantic task categories. Converging activation among three language-processing components was found in the left middle frontal gyrus, the left superior parietal lobule and the left mid-fusiform gyrus, suggesting a common sub-network underlying the character recognition process regardless of the task nature. With increasing task demands, the left inferior parietal lobule and the right superior temporal gyrus were specialized for phonological processing, while the left middle temporal gyrus was involved in semantic processing. Functional dissociation was identified in the left inferior frontal gyrus, with the posterior dorsal part for phonological processing and the anterior ventral part for semantic processing. Moreover, bilateral involvement of the ventral occipito-temporal regions was found for both phonological and semantic processing. The results provide better understanding of the neural networks underlying Chinese orthographic, phonological, and semantic processing, and consolidate the findings of additional recruitment of the left middle frontal gyrus and the right fusiform gyrus for Chinese character processing as compared with the universal language network that has been based on alphabetic languages.
越来越多的神经影像学证据表明，由于汉字独特的语言特征，其处理过程需要与字母语言不同的激活方式。随着最近对汉字处理的研究越来越多，我们采用元分析方法来总结以往的研究结果，并分别检查汉字的正字法、语音和语义处理的神经网络。激活似然估计（ALE）方法用于分析正字法任务类别中的 8 项研究、语音任务类别中的 11 项研究和语义任务类别中的 15 项研究。在左中央额回、左顶叶上回和左中梭状回中发现了三个语言处理成分之间的汇聚激活，这表明无论任务性质如何，字符识别过程都有一个共同的子网。随着任务需求的增加，左顶下小叶和右颞上回专门用于语音处理，而左颞中回则参与语义处理。在左额下回发现了功能分离，后部背侧部分用于语音处理，前部腹侧部分用于语义处理。此外，还发现双侧腹侧枕颞区参与了语音和语义处理。研究结果更好地理解了汉字正字法、语音和语义处理的神经网络，并巩固了与基于字母语言的通用语言网络相比，左中央额回和右侧梭状回对汉字处理的额外招募的发现。
