There is a growing body of research demonstrating that the cerebellum is involved in language understanding. Early theories assumed that the cerebellum is involved in low-level language processing. However, those theories are at odds with recent work demonstrating cerebellar activation during cognitive tasks. Using natural language stimuli and an encoding model framework, we performed an fMRI experiment where subjects passively listened to five hours of natural language stimuli which allowed us to analyze language processing in the cerebellum with higher precision than previous work. We used this data to fit voxelwise encoding models with five different feature spaces that span the hierarchy of language processing from acoustic input to high-level conceptual processing. Examining the prediction performance of these models on separate BOLD data shows that cerebellar responses to language are almost entirely explained by high-level conceptual language features rather than low-level acoustic or phonemic features. Additionally, we found that the cerebellum has a higher proportion of voxels that represent social semantic categories, which include "social" and "people" words, and lower representations of all other semantic categories, including "mental", "concrete", and "place" words, than cortex. This suggests that the cerebellum is representing language at a conceptual level with a preference for social information.

中文翻译：

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Voxelwise编码模型表明小脑语言表示具有很高的概念性

越来越多的研究表明小脑与语言理解有关。早期的理论假设小脑参与了低级语言处理。但是，这些理论与最近的研究表明认知任务期间小脑激活的研究相矛盾。使用自然语言刺激和编码模型框架，我们进行了功能磁共振成像实验，受试者被动听了五个小时的自然语言刺激，这使我们能够以比以前的工作更高的精度分析小脑中的语言处理。我们使用此数据来拟合具有五个不同特征空间的体素编码模型，这些特征空间跨越了从声音输入到高级概念处理的语言处理层次结构。在单独的BOLD数据上检查这些模型的预测性能表明，小脑对语言的反应几乎完全由高级概念性语言特征而非低级声学或音素特征来解释。此外，我们发现小脑具有较高的代表社会语义类别的体素比例，其中包括“社会”和“人”字，而所有其他语义类别的代表则较低，包括“心理”，“具体”和“地方”这句话，胜过皮质。这表明小脑在概念上代表语言，并且偏爱社交信息。