Language represents a higher-order cognitive function unique to humans and occupies a central position within the brain’s advanced functional systems. Consequently, elucidating the neural mechanisms that underlie the emergence, development, and aging of language is of profound significance for advancing our understanding of both language itself and the operational principles of the human brain.

     Our research group is dedicated to delineating the structural and functional architecture of the neural network supporting Chinese language processing, and to examining how experience-driven learning shapes its plasticity. Through this work, we aim to uncover the developmental principles governing the Chinese language network.

         语言是人类特有的高级功能,在人脑高级功能系统中占据核心地位。因此,揭示语言的形成、发展和老化的认知神经机制,对于探讨语言本身以及人脑的工作原理具有重要的价值。课题组致力于构建汉语认知神经结构和功能网络,并分析后天学习经验对该网络的可塑性影响,从而揭示汉语神经网络的发生发展规律。



Research 1

The brain-specific network for processing Chinese  pictographs

汉语象形文字加工的大脑特异性网络

Chinese pictographs are visually identical stimuli that can be interpreted either as words (lexical symbols) or as objects (visual depictions) and that were rigorously matched in a visual form, phonology, and semantics. Taking advantage of this characteristic, having the participants perceive the pictographic characters as words and objects during the task can be used to examine the core differences in the processing of word and object recognition. Results revealed robust word–object differences in the inferior parietal lobule (IPL), anterior cingulate cortex (ACC), and their associated networks. Compared with object recognition, word recognition elicited stronger activation in the IPL and reduced deactivation in the ACC. Furthermore, both regions exhibited distinct multivoxel activation patterns between the word and object recognition and showed stronger functional connectivity with other brain regions specifically during word recognition.

        汉字象形符号在视觉上是完全相同的视觉个体,既可以被解读为单词(词汇符号),也可以被解读为物体(视觉描绘),并且在视觉形式、语音学和语义方面都经过了严格的匹配。利用这一特性,在fMRI中让参与者将象形字符视为单词和物体,可以用来研究单词和物体识别处理过程中的核心差异。结果表明,在下顶叶(IPL)、前扣带回皮层(ACC)及其相关网络中存在明显的单词与物体的差异。


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Figure: The stimuli and procedure for Chinese pictograph tasks.


Major findings:

Zeng, J., Luo, Y., Luo, X., Jiao, S., Wang, K., Cui, Z., ... & Han, Z.* (2025). Neural distinction between visual word and object recognition: An fMRI study using pictographs. Journal of Neuroscience, 45(28). PDF


Research 2

White-Matter Structural Networks Underlying Chinese Language Processing

汉语加工的脑白质结构网络

By integrating behavioral performance on Chinese language tasks with diffusion tensor imaging data, we constructed white-matter fiber networks supporting orthographic, phonological, and semantic processing in Chinese. Our findings reveal that the semantic network constitutes a complex architecture formed by multiple fiber bundles, among which the tract connecting the left fusiform gyrus and the collateral sulcus conveys color-related conceptual knowledge of objects. The phonological network comprises major pathways such as the left superior longitudinal fasciculus (SLF), the anterior thalamic radiation (ATR), and the inferior fronto-occipital fasciculus (IFOF), whereas the left inferior longitudinal fasciculus (ILF) predominantly transmits orthographic information. Moreover, we delineated the spatial intersections between the language network and other cognitive systems, including the executive-control network.

         通过对汉语加工测试成绩与弥散张量成像数据的相关分析,构建起了加工汉语形、音、义的白质纤维网络。主要发现,语义网络是由多条纤维束组成的复杂网络,其中左侧梭状回-距状裂之间的纤维束传递物体语义的颜色类知识。左侧上纵束(SLF)、丘脑放射前束(ATR)、下额枕束(IFOF)等组成语音加工网络,而左侧下纵束(ILF)传递字形信息。同时,还描绘出了语言网络与其他认知网络(如执行控制网络)的交叠情况。


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Figure:The semantic hub region in patients with semantic dementia.

A) The left lateral fusiform gyrus (LFFG, highlighted in red) identified as the central semantic hub and its nine connected cortical regions.
B) The association between the node degree of the left fusiform gyrus and performance on semantic tasks.



Major findings:

Chen Y#, Huang L#, Chen K, Ding J, Zhang Y, Qing Y, Lv Y, Han Z*, Qihao Guo*. (2020). White matter basis for the hub-and-spoke semantic representation: evidence from semantic dementia. Brain, 143: 1206-1219. PDF

Ke Wang, Xiaonan Li, Ruiwang Huang, Junhua Ding, Luping Song, Zaizhu Han*. (2020). The left inferior longitudinal fasciculus supports orthographic processing: Evidence from a lesion-behavior mapping analysis. Brain and Language, 201:104721 PDF

Ding J#, Chen K#, Zhang W, Li M, Chen Y, Yang Q, Lv Y, Guo Q*, Han Z*. (2017). Topological Alterations and Symptom-Relevant Modules in the Whole-Brain Structural Network in Semantic Dementia. Journal of Alzheimer’s Disease, 59: 1283-1297. PDF

Li M, Zhang Y, Song L, Huang R, Ding J, Fang Y, Xu Y, Han Z*. (2017). Structural connectivity subserving verbal fluency revealed by lesion-behavior mapping in stroke patients. Neuropsychologia, 101: 85-96.  PDF

Bi Y, Han Z*, Zhong S, Ma Y, Gong G, Huang R, Song L, Fang Y, He Y, Caramazza A. (2015). The white matter structural network underlying human tool use and tool understanding. The Journal of Neuroscience, 35: 6822-6835. PDF



Research 3

Gray-matter functional network for Chinese language processing

汉语加工的脑灰质功能网络


Using correlation analyses between behavioral performance on Chinese language tasks and three-dimensional gray-matter imaging as well as resting-state functional neuroimaging data, we identified the key hub regions underlying Chinese language processing and reconstructed the corresponding functional network. The major findings indicate that the left temporal lobe, hippocampus, and cingulate gyrus constitute critical hub regions. Building on these discoveries, we further developed computational models of anterior temporal-lobe function that account for the processing of different categories of information (e.g., language, face recognition, and disinhibition).

Anchored on these core language-related regions, we employed functional connectivity analyses to delineate the brain network supporting Chinese language processing. Notably, hippocampal connectivity with the anterior temporal lobe and middle temporal gyrus was found to support semantic processing; connectivity between the precuneus and the parahippocampal gyrus, inferior temporal gyrus, and inferior/middle frontal gyri was implicated in noun processing; whereas connectivity between the middle/superior temporal gyri and the inferior frontal gyrus/insula and middle occipital gyrus was implicated in verb processing.

        通过对汉语加工测试成绩和灰质3D、功能态神经影像学数据的相关分析,找到了加工汉语的关键hub脑区,并构建了与此对应的功能网络。主要发现,左脑颞叶、海马、扣带回是的关键hub脑区,并对构建了颞叶前部加工不同类信息(如,语言、面孔识别、去抑制)的神经计算模型。以这些关键语言脑区为核心,通过功能连接分析技术,建立了语言加工的脑功能网络。其中,发现海马与颞叶前部、颞中回的功能连接参与语义加工;楔前叶与海马旁回、颞下回、额下回/额中回的功能连接参与名词加工,而颞中回/颞上回与额下回/脑岛、枕中回的功能连接参与动词加工。


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Figure. Comparative correlations between bilateral anterior temporal-lobe regions

and different semantic performance measures.



Major findings:

Ding J#, Chen K#, Liu H, Huang L, Chen Y, Ying R, Yang Q, Guo Q*, Han Z*, Lambon Ralph M*. (2020). A unified neurocognitive model of semantics language social behaviour and face recognition in semantic dementia. Nature Communications, 11: 2595.  PDF

Chen Y#, Chen K#, Ding J, Zhang Y, Yang Q, Lv Y, Guo Q, Han Z*. (2019). Neural substrates of amodal and modality-specific semantic processing within the temporal lobe: A lesion-behavior mapping study of semantic dementia. Cortex, 120: 78-91. PDF

Zhao Y, Song L, Ding J, Lin N, Wang Q, Du X, Sun R, Han Z*. (2017). Left anterior temporal lobe and bilateral anterior cingulate cortex are semantic hub regions: evidence from behavior-nodal degree mapping in brain-damaged patients. The Journal of Neuroscience, 37: 141-151. PDF

Chen Y, Chen K, Ding J, Zhang Y, Yang Q, Lv Y, Guo Q, Han Z. (2017). Brain Network for the Core Deficits of Semantic Dementia: A Neural Network Connectivity-Behavior Mapping Study. Front Hum Neurosci.11:267. PDF

CAoCA汉语失语症认知评估系统软件V1.0 (CAoCA Chinese Aphasia Cognitive Assessment System Software v1.0)


Research 4

Plasticity of the Chinese Language Neural Network

汉语神经网络的可塑性变化规律

    To investigate how experience-dependent learning shapes the plasticity and developmental trajectory of the neural network for language, our research group conducted training experiments in which healthy adults learned novel symbols as Chinese characters, as well as fMRI studies in individuals with congenital sensory deprivation. The results showed that when meaningless visual forms were trained to be recognized as Chinese characters or as objects, the visual word form area (VWFA) exhibited selective activation only for items learned as characters. Moreover, functional connectivity between the VWFA and other higher-order language regions was strengthened following character learning.

    Compared with neurotypical individuals, congenital deaf participants showed markedly reduced functional connectivity between the VWFA and the auditory speech region (left superior temporal gyrus). Congenitally blind individuals also exhibited distinct VWFA connectivity patterns relative to sighted controls. These findings demonstrate that the neural network for Chinese language develops through the joint contributions of both innate and experience-dependent factors.

        为了探讨语言神经网络受后天学习经验的可塑性影响及其发展变化规律,课题组开展了正常人的学习汉字训练实验和先天感觉通道缺失个体的功能磁共振成像(fMRI)实验。结果发现,当把无意义图形学习为汉字和物体时,字形加工脑区(VWFA)只有对学习为汉字的试次出现选择性激活,而且这个脑区和其他高级语言区的功能连接也有所增强。与正常人相比,先天聋人的这一脑区与听觉言语区(左侧颞上回)之间的功能连接明显减弱,先天盲人这一区域与其他脑区的功能连接模式也与正常人存在差异。这些结果表明,汉语的神经网络在先天和后天因素共同作用下协同发展。


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Figure. Pre- and post-training comparison of VWFA activation

when novel objects are learned as characters versus as objects.



Major findings:

Li M, Xu Y, Luo X, Zeng J, Han Z*. (2020). Linguistic experience acquisition for novel stimuli selectively activates the neural network of the visual word form area. Neuroimage, 215: 116838.  PDF

Wang, X., Peelen, M. V., Han, Z., He, C., Caramazza, A., & Bi, Y.. (2015). How visual is the visual cortex? comparing connectional and functional fingerprints between congenitally blind and sighted individuals. Journal of Neuroscience the Official Journal of the Society for Neuroence, 35(36), 12545. PDF

Xiaosha, W., Alfonso, C., Peelen, M. V., Zaizhu, H., & Yanchao, B.. (2015). Reading without speech sounds: vwfa and its connectivity in the congenitally deaf. Cerebral Cortex (9), 2416. PDF

Zheng, L., Chen, C., Liu, W., Long, Y., & Lu, C.. (2018). Enhancement of teaching outcome through neural prediction of the students' knowledge state. Human Brain Mapping, 39(2), 3046.  PDF