王婧 - 华东师范大学 - 心理与认知科学学院

个人简介

华东师范大学心理与认知科学学院晨晖学者。主要研究方向是概念与知识的神经表征，通过fMRI等神经影像学技术探索如何通过脑活动解码思想。在University of South Carolina获得博士学位，在Carnegie Mellon University接受博士后训练。主持项目国家自然科学基金青年项目：抽象概念的隐喻化神经表征，2022-2024

研究领域

从方法论的角度，关注如何通过fMRI等手段测量的脑活动解码思想从科学主题的角度，关注概念的产生与表征机制，知识的神经组织规律，语言能力的认知神经基础

近期论文

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Wang J.*, Lin H., & Cai Q.* (2023) How Grammar Conveys Meaning: Language-specific spatial encoding patterns and cross-language commonality in higher-order neural space. Journal of Neuroscience. doi: 10.1523/JNEUROSCI.0599-23.2023 Zhang R. ǂ, Wang J. ǂ, Lin H., Turk-Browne N.B., & Cai Q.* (2023) Neural signatures of second language proficiency in narrative processing. Cerebral Cortex. (ǂEqual contribution) Li L., Zhao W., Song M., Wang J.*, & Cai Q.* (2023) CCLOOW: Chinese children’s lexicon of oral words. Behavior Research Methods. doi: 10.3758/s13428-023-02077-6 Feng J., Mak H.Y., Wang J.*, & Cai Q.* (2022) How characters are learned leaves its mark on the neural substrates of Chinese reading. eNeuro 9: ENEURO.0111-22.2022 Gao C., Baucom L.B., Kim J., Wang J., Wedell D.H., & Shinkareva S.V. (2019) Distinguishing abstract from concrete concepts in supramodal brain regions. Neuropsychologia 131:102–110 Wang J., Cherkassky V.L., & Just M.A. (2017) Predicting the brain activation pattern associated with the propositional content of a sentence: modeling neural representations of events and states. Human Brain Mapping. 38(10). doi: 10.1002/hbm.23692 Just M.A.ǂ, Wang J.ǂ, & Cherkassky, V.L. (2017) Neural representations of the concepts in simple sentences: concept activation prediction and context effects. Neuroimage. 157: 511-520. (ǂEqual contribution) Yang Y., Wang J., Bailer C., Cherkassky V.L., & Just M.A., (2017) Commonalities and differences in the neural representations of English, Portuguese, and Mandarin sentences: when knowledge of the brain-language mappings for two languages is better than one. Brain and Language. 175: 77-85. Wang J., Cherkassky V.L., Yang Y., Chang K.K., Vargas R., Diana N., & Just M.A. (2016) Identifying object’s thematic role in an event from fMRI-measured neural representation. Cognitive Neuropsychology. doi:10.1080/02643294.2016.1182480 Yang Y., Wang J., Bailer C., Cherkassky V., & Just M.A. (2016) Commonality of neural representations of sentences across languages: predicting brain activation during Portuguese sentence comprehension using an English-based model of brain function. Neuroimage. 146: 658-666. Kim J., Wang J., Wedell D.H., & Shinkareva S.V. (2016) Identifying core affect in individuals from fMRI responses to dynamic naturalistic audiovisual stimuli. PLoS ONE11(9): e0161589. Shinkareva S.V., Wang J., Kim J., Facciani M.J., Baucom L.B., & Wedell D.H. (2014) Representations of modality-specific affective processing for visual and auditory stimuli derived from fMRI data. Human Brain Mapping. 35: 3558-3568 Wang J., Baucom L.B., & Shinkareva S.V. (2013) Decoding abstract and concrete concept representation based on single-trial fMRI data. Human Brain Mapping. 34: 1133-1147 Shinkareva S.V., Wang J., & Wedell, D.H. (2013) Examining similarity structure: Multidimensional scaling and related approaches in neuroimaging. Computational and Mathematical Methods in Medicine. doi:10.1155/2013/796183 Henderson J.M., Shinkareva S.V., Wang J., Luke S.G., & Olejarczyk J. (2013) Predicting cognitive states from eye movements. PLoS ONE8(5): e64937 Baucom L.B., Wedell D.H., Wang J., Blitzer D.N., & Shinkareva S.V. (2012) Decoding the neural representation of affective states. Neuroimage. 59: 718-727 Murdaugh D.L., Shinkareva S.V., Deshpande H.R., Wang J., Pennick M.R., & Kana R.K. (2012) Differential deactivation during mentalizing and classification of autism based on default mode network connectivity. PLoS ONE 7(11): e50064. Wang J., Conder J.A., Blitzer D.N., & Shinkareva S.V. (2010) Neural representation of abstract and concrete concepts: a meta-analysis of neuroimaging studies. Human Brain Mapping. 31: 1459-1468 Shinkareva S.V., Gudkov V., & Wang J. A Network Analysis Approach to fMRI Condition-Specific Functional Connectivity. arXiv:1008.0590v1 (2010).