Abstract： An increasing interest has focused on unifying the cognitive and neurobiological models of language processing with mounting evidence reported in recent years. A bottleneck problem emerged out to reveal the neural circuit of semantic processing. However, this issue remains unresolved because of the limitation of alphabetic languages. Taking the advantage of systematic mapping from orthography to meaning in Chinese characters, the proposed project aims to investigate the neural circuit of semantic processing and its cooperative division of labor with the neural circuit of phonological processing in reading Chinese characters. Study 1 is designed to identify the function regions involved in Chinese character reading by correlating the BOLD signal with the time series coding of stimulus properties. Study 2 focuses on the neural circuit of semantic processing. The first step is to examine the neural mechanism for the processing of semantic components and its influence on the processing of whole characters’ meaning. The further analysis is to investigate the nature of the involving of prior semantic related brain regions in the processing of semantic components. Study 3 adapts the Dynamic Causal Model (DCM) to examine the patterns of the connectivity among regions of reading network driven both by the stimulus properties and task demands. The expected findings will reveal the dynamic of the cooperation between the neural circuits of semantic and phonological processing. The results can provide evidence in unifying the cognitive and neurobiological models of language processing. Also, the results will provide theoretical guidance for empirical studies and applications, such as language teaching, treatment of reading disorders and clinical diagnoses.
杨剑峰, 党敏, 张瑞, 王小娟. 汉字阅读的语义神经回路及其与语音回路的协作机制[J]. 心理科学进展, 2018, 26(3): 381-390.
YANG Jianfeng, DANG Min, ZHANG Rui, WANG Xiaojuan. The neural circuit of semantic processing and its dynamic cooperation with the neural circuit of phonological processing in reading Chinese characters. Advances in Psychological Science, 2018, 26(3): 381-390.