Publications

Li, J., Wang, Q., Wang, Y., Wang, C., Ma, Z., Xu, R., Feng, S., Jiang, X. & Meng, Z. (in revision). BABA: fMRI and MEG recordings during viewing of a multi-speaker TV show. [OpenNeuro] [bioRxiv]

Gao, C., Ma Z., Chen J., Li, P., Huang, S. & Li, J. (accepted). Scaling, but not instruction tuning, increases large language models’ alignment with language processing in the human brain. Nature Computational Science. [bioRxiv]

Wang, Q., Zhou, Q., Ma, Z., Wang, N., Zhang, T., Fu, Y. & Li, J. (2025). Le Petit Prince (LPP) Multi-talker: Naturalistic 7T fMRI and EEG dataset. Scientific Data. 12, 1. [OpenNeuro] [DOI]

Momenian, M., Ma, Z., Wu, S., Wang, C., Vaghefi, M., Hale, J., Brennan, J., Meyer, L, & Li, J. (2024). Le Petit Prince Hong Kong (LPPHK): Naturalistic fMRI and EEG dataset from older Cantonese. Scientific Data. 11, 992. [OpenNeuro] [DOI]

Book Chapter

Li, J., Ma, Z., & Wang, C. (under review). MRI datasets for language processing. in Nesi, H., and Milin, P. (Eds.). International Encyclopedia of Language and Linguistics, 3rd Edition. Elsevier.

Conference Presentations

Ma, Z., Gao, Q., Wang, N., & Li J. (2025). Neural tracking of semantic and rhythmic information under temporal compression. Poster at the 18th Annual Meeting of Chinese Neuroscience Society (CNS 2025), Xi’an, China, September 25-28, 2025.

Ma, Z., Gao, Q., Wang, N., & Li J. (2025). Neural tracking of semantic and rhythmic information under temporal compression. Poster at Society for the Neurobiology of Language 17th Annual Meeting (SNL 2025), Washington, D.C., USA, September 12-14, 2025.

Ma, Z., Wang, N., & Li J. (2025). Le Petit Prince (LPP) Multi-talker: Naturalistic 7T fMRI and EEG Dataset. Poster at the International Workshop on Cross-linguistic Databases and Norms, Shanghai, China, May 31-June 1, 2025.

Ma Z. & Li J. (2024). Modeling the trajectory of language processing in neural state space. Poster at Society for the Neurobiology of Language 16th Annual Meeting (SNL 2024), Brisbane, Australia, October 24-26, 2024.

Ma Z., Wang C. & Li J. (2023). Syntactic information drives language models’ alignment with human comprehension processes. Oral presented at the Architectures and Mechanisms for Language Processing (AMLaP Asia), Hong Kong, December 1-3, 2023.

Ma Z. & Huang Y. (2023). Do language models follow dependency distances in text reading like humans? Oral presented at the 2nd Conference on Data Science & L2 Studies, Shanghai, China, November 3-5, 2023.

Ma Z. (2023). Testing the relationship of lexical complexity to the rated quality of TEM-4 oral narratives. Oral presented at the Pacific Second Language Research Forum (PacSLRF), Bangkok, Thailand, July 26-27, 2023.

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