Computational Models to Study Language Processing in the Human Brain: A Survey

• URL: http://arxiv.org/abs/2403.13368v1
• Date: Wed, 20 Mar 2024 08:01:22 GMT
• Title: Computational Models to Study Language Processing in the Human Brain: A Survey
• Authors: Shaonan Wang, Jingyuan Sun, Yunhao Zhang, Nan Lin, Marie-Francine Moens, Chengqing Zong,
• Abstract summary: This paper reviews efforts in using computational models for brain research, highlighting emerging trends. Our analysis reveals that no single model outperforms others on all datasets.
• Score: 47.81066391664416
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Despite differing from the human language processing mechanism in implementation and algorithms, current language models demonstrate remarkable human-like or surpassing language capabilities. Should computational language models be employed in studying the brain, and if so, when and how? To delve into this topic, this paper reviews efforts in using computational models for brain research, highlighting emerging trends. To ensure a fair comparison, the paper evaluates various computational models using consistent metrics on the same dataset. Our analysis reveals that no single model outperforms others on all datasets, underscoring the need for rich testing datasets and rigid experimental control to draw robust conclusions in studies involving computational models.

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