Department of Chinese and Bilingual Studies, The Hong Kong Polytechnic University, Hung Hom, Hong Kong.
Research Institute for Smart Ageing (RISA), The Hong Kong Polytechnic University, Hung Hom, Hong Kong.
Sci Data. 2024 Sep 11;11(1):992. doi: 10.1038/s41597-024-03745-8.
Currently, the field of neurobiology of language is based on data from only a few Indo-European languages. The majority of this data comes from younger adults neglecting other age groups. Here we present a multimodal database which consists of task-based and resting state fMRI, structural MRI, and EEG data while participants over 65 years old listened to sections of the story The Little Prince in Cantonese. We also provide data on participants' language history, lifetime experiences, linguistic and cognitive skills. Audio and text annotations, including time-aligned speech segmentation and prosodic information, as well as word-by-word predictors such as frequency and part-of-speech tagging derived from natural language processing (NLP) tools are included in this database. Both MRI and EEG data diagnostics revealed that the data has good quality. This multimodal database could advance our understanding of spatiotemporal dynamics of language comprehension in the older population and help us study the effects of healthy aging on the relationship between brain and behaviour.
目前，语言神经生物学领域的研究数据主要来自于几种印欧语系的语言。这些数据大多数来自于年轻人，而忽视了其他年龄段的人群。在这里，我们提供了一个多模态数据库，其中包括任务态和静息态 fMRI、结构 MRI 和 EEG 数据，同时让 65 岁以上的参与者听粤语版的《小王子》的节选内容。我们还提供了参与者的语言历史、生活经历、语言和认知技能的数据。该数据库包括音频和文本注释，包括与时间对齐的语音分割和韵律信息，以及通过自然语言处理（NLP）工具得出的词频和词性标注等逐字预测器。MRI 和 EEG 数据诊断表明，该数据质量良好。这个多模态数据库可以帮助我们深入理解老年人语言理解的时空动态，并研究健康老龄化对大脑与行为之间关系的影响。
