Neural Pattern Similarity in Chinese Character Processing Using Representational Similarity Analysis: A Review and Future Directions

DOI

10.2991/978-94-6239-630-2_26How to use a DOI?

Keywords

Chinese Character Learning; Representational Similarity Analysis; Visual Word Form Area

Abstract

It is important to explore the neural patterns involved in Chinese character processing since its learning poses major challenges for foreign language learners. However, most studies on this topic have relied on univariate activation analysis. Very few studies have adopted representational similarity analysis (RSA) that is able to capture fine-grained pattern differences even when regional-average differences are absent ^[1]. This paper systematically reviews studies using RSA and suggests that the Visual Word Form Area (VWFA) is crucial in Chinese character processing, as it simultaneously represents phonological, orthographic, and semantic information. Furthermore, the review proposes two directions for future research: (1) investigating how language-related factors affect neural patterns through a longitudinal design; and (2) exploring whether large language models (LLMs) process Chinese characters similarly to humans. This review provides theoretical support for advancing the understanding of the neural mechanisms involved in Chinese character processing and may contribute to the development of AI-assisted educational technologies and personalized learning tools for Chinese character learning.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zhongshi Li
PY  - 2026
DA  - 2026/04/23
TI  - Neural Pattern Similarity in Chinese Character Processing Using Representational Similarity Analysis: A Review and Future Directions
BT  - Proceedings of the 2025 International Conference on Educational Technology and Management Information Systems (ETMIS 2025)
PB  - Atlantis Press
SP  - 267
EP  - 273
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-630-2_26
DO  - 10.2991/978-94-6239-630-2_26
ID  - Li2026
ER  -