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<p>Language is the primary medium through which humans achieve information transfer and exchange. It enables the conveyance of ideas, concepts, and messages, thereby playing an indispensable role in social interaction and knowledge dissemination. Linguistic neural decoding aims to obtain outstanding language information from the evoked human brain during information interaction of both textual and spoken formats. In this work, we present a taxonomy of recent neural decoding progress, focusing on deep learning architectures and strategies, especially those implementing large language models (LLMs) for their powerful information understanding, processing, and generation capacity. We conclude with a concise observation of the challenges and potential future directions. This article aims to provide brain scientists and deep learning researchers with an overarching viewpoint of the significant correlations observed in the human brain during language perception and production from a methodological perspective, and thus facilitate their further investigation.</p>

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Progress, challenges and future of linguistic neural decoding with deep learning

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月24日

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  • Yu Wang,
  • Heyang Liu,
  • Yuhao Wang,
  • Chuan Xuan,
  • Yixuan Hou,
  • Sheng Feng,
  • Hongcheng Liu,
  • Yusheng Liao,
  • Yanfeng Wang

摘要

Language is the primary medium through which humans achieve information transfer and exchange. It enables the conveyance of ideas, concepts, and messages, thereby playing an indispensable role in social interaction and knowledge dissemination. Linguistic neural decoding aims to obtain outstanding language information from the evoked human brain during information interaction of both textual and spoken formats. In this work, we present a taxonomy of recent neural decoding progress, focusing on deep learning architectures and strategies, especially those implementing large language models (LLMs) for their powerful information understanding, processing, and generation capacity. We conclude with a concise observation of the challenges and potential future directions. This article aims to provide brain scientists and deep learning researchers with an overarching viewpoint of the significant correlations observed in the human brain during language perception and production from a methodological perspective, and thus facilitate their further investigation.