Le Petit Prince multilingual fMRI corpus (ds003643)
Le Petit Prince: A multilingual fMRI corpus using ecological stimuli (LPPC-fMRI)
Multi-echo fMRI and T1-weighted MRI of healthy young English, Chinese and French speakers listening to The Little Prince audiobook in their native language, with word-level speech and linguistic annotations for cross-language studies of comprehension.
Overview
The Le Petit Prince fMRI Corpus (LPPC-fMRI) records brain activity of young adults while they hear the whole of The Little Prince read aloud in their native language, in English, Chinese or French. Because all three groups heard the same story, the corpus supports comparing how language comprehension unfolds across typologically different languages. Groups at Cornell University, Jiangsu Normal University and NeuroSpin shared it on OpenNeuro as ds003643 under a CC0 waiver in 2021 and described it in Scientific Data in 2022. A separate release of the same paradigm with older Cantonese speakers is indexed as Le Petit Prince Hong Kong.
Composition
The corpus holds 112 healthy, right-handed native speakers: 49 English (30 female), 35 Chinese (15 female) and 28 French (15 female), aged 18 to 40. Every subject has one T1-weighted image and nine story-listening runs of about ten minutes each, one per section of the audiobook; two subjects have extra runs. participants.tsv adds quiz accuracy for the English and Chinese groups.
Acquisition
The English and Chinese groups were scanned on a 3 T GE Discovery MR750 with a 32-channel coil, the French group on a 3 T Siemens Magnetom Prisma Fit. Anatomy is a 1 mm MPRAGE. Functional runs use multi-echo EPI with three echoes, a 2 s repetition time and 3.75 x 3.75 x 3.8 mm voxels. English and Chinese subjects were scanned in a single session of about 2.5 hours and answered four comprehension questions after each run; French subjects were scanned in two sessions because of a legal limit on time in the scanner. Identifying anatomical information was removed before release.
Annotations
There are no image labels. Each language comes with word boundaries aligned to the audio, pitch and intensity every 10 ms, word frequency, lemmas and part-of-speech tags, GloVe and BERT embeddings, constituency and dependency parses, and, for English and Chinese, coreference annotations. Derivatives hold AFNI-preprocessed, multi-echo denoised functional runs in MNI space for all 112 subjects.
Known limitations
- The three groups differ in scanner, site, headphones and session structure, which confounds language with site.
- Earlier work on the English data used 51 subjects; 49 were released after excluding two for head movement.
- The paper's Table 2 gives a mean age of 19.9 for the Chinese group while its text gives 19.3; participants.tsv matches 19.9.
- Raw run numbers vary between subjects; the authors kept consistent numbering through renamed links.
Cohort
Aggregate numbers from the sources below. Bars are relative to the 112 subjects.
Sex
- Female 60 54%
- Male 52 46%
Table 2 in Li et al. 2022, Le Petit Prince multilingual naturalistic fMRI corpus, Scientific Data; sex column in participants.tsv of ds003643 2.0.7 (CC0), counted per row from the participant_id, age and sex columns
Contrast / sequence
Groups can overlap
- T1-weighted 112 100%
- BOLD fMRI 112 100%
sub-*/anat/*_T1w.nii.gz, sub-*/func/*_bold.nii.gz in File listing of ds003643 2.0.7 (CC0), counted from sub-*/anat and sub-*/func NIfTI files
Scanner vendor
- GE HealthCare 84 75%
- Siemens Healthineers 28 25%
Table 3 in Li et al. 2022, Le Petit Prince multilingual naturalistic fMRI corpus, Scientific Data
Country
- United States 49 44%
- China 35 31%
- France 28 25%
Table 2 in Li et al. 2022, Le Petit Prince multilingual naturalistic fMRI corpus, Scientific Data
Age
mean 21.6 ± 3.8, range 18 to 40
age column in participants.tsv of ds003643 2.0.7 (CC0), counted per row from the participant_id, age and sex columns
Condition
Groups can overlap
- Healthy control 112 100%
Methods: Participants in Li et al. 2022, Le Petit Prince multilingual naturalistic fMRI corpus, Scientific Data
Field strength
- 3 T 112 100%
Table 3 in Li et al. 2022, Le Petit Prince multilingual naturalistic fMRI corpus, Scientific Data
Country by sex
Reported cross table. A dot marks a cell the source does not give.
| Female | Male | |
|---|---|---|
| United States | 30 | 19 |
| China | 15 | 20 |
| France | 15 | 13 |
Table 2 in Li et al. 2022, Le Petit Prince multilingual naturalistic fMRI corpus, Scientific Data; participant_id prefix EN and sex column, participant_id prefix CN and sex column, participant_id prefix FR and sex column in participants.tsv of ds003643 2.0.7 (CC0), counted per row from the participant_id, age and sex columns
Age by sex
Reported cross table. Missing cells were not published (fewer than 10 or not reported).
- 3820-2936
- 1910-1913
age and sex columns in participants.tsv of ds003643 2.0.7 (CC0), counted per row from the participant_id, age and sex columns
Contrast combinations
How many subjects have exactly each set of contrasts.
| T1w | bold | Subjects with exactly this set |
|---|---|---|
112 |
sub-*/anat and sub-*/func in File listing of ds003643 2.0.7 (CC0), counted from sub-*/anat and sub-*/func NIfTI files
Age by country
Reported cross table. A dot marks a cell the source does not give.
| United States | China | France | |
|---|---|---|---|
| 10-19 | 15 | 15 | · |
| 20-29 | 32 | 20 | 22 |
participant_id prefix and age column in participants.tsv of ds003643 2.0.7 (CC0), counted per row from the participant_id, age and sex columns
License and access
Our reading of the license, not legal advice. Before you use the data, read the original license and confirm that your use is allowed. We take no responsibility for how you use a dataset. Full disclaimer
Download without an account
Creative Commons Zero 1.0 Universal
Public domain dedication. Do anything with the data, including commercial use, without asking and without having to give credit.
dataset_description.json of snapshot 2.0.7 states "License" CC0.
What you can do
- Yes
- Yes
- Yes
- Yes
- Yes
What you can share
- Yes
- Yes
- Yes
What you must do
- No
- Share alike No
- No
- No
- Manuscript review No
- Release code No
- Return results No
- Delete after use No
Limits
- No
- Location limits No
Citation
Li J, Bhattasali S, Zhang S, Franzluebbers B, Luh W, Spreng RN, Brennan JR, Yang Y, Pallier C, Hale J. Le Petit Prince multilingual naturalistic fMRI corpus. Scientific Data 9, 530 (2022). doi:10.1038/s41597-022-01625-7
Sources
Every number on this page comes from one of these documents. Each chart names the table or page it is taken from. The raw numbers are in stats.csv.
- Li et al. 2022, Le Petit Prince multilingual naturalistic fMRI corpus, Scientific Data paper
- OpenNeuro ds003643 snapshot 2.0.7 (dataset_description.json, README, CHANGES and snapshot summary) website
- participants.tsv of ds003643 2.0.7 (CC0), counted per row from the participant_id, age and sex columns computed
- File listing of ds003643 2.0.7 (CC0), counted from sub-*/anat and sub-*/func NIfTI files computed