Efforts to understand the brain bases of language face the Mapping Problem: At what level do linguistic computations and representations connect to human neurobiology? We review one approach to this problem that relies on rigorously defined computational models to specify the links between linguistic features and neural signals. Such tools can be used to estimate linguistic predictions, model linguistic features, and specify a sequence of processing steps that may be quantitatively fit to neural signals collected while participants use language. Progress has been helped by advances in machine learning, attention to linguistically interpretable models, and openly shared data sets that allow researchers to compare and contrast a variety of models. We describe one such data set in detail in the Supplemental Appendix .

中文翻译：

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语言处理的神经计算模型

理解语言大脑基础的努力面临映射问题：语言计算和表示在什么级别与人类神经生物学相关联？我们回顾了一种解决这个问题的方法，该方法依赖于严格定义的计算模型来指定语言特征和神经信号之间的联系。此类工具可用于估计语言预测、建模语言特征，并指定一系列处理步骤，这些步骤可能在数量上适合参与者使用语言时收集的神经信号。机器学习的进步、对语言可解释模型的关注以及允许研究人员比较和对比各种模型的公开共享数据集都有助于取得进展。我们在补充附录中详细描述了一个这样的数据集。