The dataset contains the following files with BIDS style.
(1) Brain imaging dataset (sub-/ses-site/{func, anat, fmap}) [NIFTI format]
- Resting-state functional image
- T1-weighted structural image
- Fieldmap (optional)
(2) README
- Explanation of dataset
(3) Participant demographic information (participants.{tsv,json})
- Including ID, age, sex
(4) Measurements information for each site/session (sub-/ses-site/sub-*_sessions.{tsv,json})
- Including session ID, site, day, phase, manufacture, coil, scanner
(5) QC results (QC/group_{bold, T1w}.tsv)
- Outputs of MRIQC for rs-fMRI and T1w
The structure of dataset (BIDS valid):
SRPBS_TS
├── sourcedata
│ ├── README
│ ├── dataset_description.json
│ ├── participants.json
│ ├── participants.tsv
│ └── sub-0*
│ ├── sub-0*_sessions.json
│ ├── sub-0*_sessions.tsv
│ ├── ses-site*
│ │ ├── func
│ │ ├── anat
│ │ └── fmap
│ ...
└── QC
├── group_T1w.tsv
└── group_bold.tsv
Please refer to our published paper for detailed methods;
- Tanaka, S.C., Yamashita, A., Yahata, N. et al. A multi-site, multi-disorder resting-state magnetic resonance image database. Sci Data 8, 227 (2021). https://doi.org/10.1038/s41597-021-01004-8
* MD5 hash : f6a991271a753e746a6f62a7444ec466
* As file size is large ( 19.5GB ), downloading takes time.
* This file is stored in Amazon S3 Service.
Program code of deface (face-masking) for anatomical MRI images
To avoid identifying individual participant by reconstruction of face surface from the structural MRI data of our datasets, we performed face-masking calculation. This code removes the subject's face from the MRI structure image (NIfTI format: .nii). This is written in MATLAB and internally uses SPM8 and mri_deface.
Github page : https://github.com/bicr-resource/deface
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