ArticleScientific data2024
Le Petit Prince Hong Kong (LPPHK): Naturalistic fMRI and EEG data from older Cantonese speakers.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning.Scientific data · 2026Article
- Towards decoding individual words from non-invasive brain recordings.Nature communications · 2025Article
- Naturalistic fMRI and MEG recordings during viewing of a reality TV show.Scientific data · 2025Article
- Le Petit Prince (LPP) multi-talker: Naturalistic 7 T fMRI and EEG dataset.Scientific data · 2025Article
- Le Petit Prince Hong Kong (LPPHK): Naturalistic fMRI and EEG data from older Cantonese speakers.Scientific data · 2024Article
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Authors and funding
8 authors.
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Abstract
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.
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