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.

翻译：尽管当前的语言模型在实现方式和算法上与人脑语言处理机制不同，但它们展现出显著的人类水平甚至超越人类的语言能力。计算语言模型能否应用于大脑研究？如果可以，应在何时以及如何应用？为深入探讨这一主题，本文综述了利用计算模型进行脑科学研究的现有工作，并指出了新兴趋势。为确保公平比较，本文采用统一指标在相同数据集上评估了多种计算模型。分析表明，没有任何单一模型在所有数据集上表现最优，这强调了在涉及计算模型的研究中，需要丰富的测试数据集和严格的实验控制才能得出稳健结论。