The dataset contains the following files.
(1) Brain imaging dataset (data/sub-*/{rsfmri, t1, fmap}) [NIFTI format]
- Resting-state functional image
- T1-weighted structural image
- Fieldmap (optional)
(2) README (README.txt)
- Explanation of dataset
(3) Participant demographic information (participants.tsv)
- Including ID, age, sex, hand, diagnosis, clinical rating scales
(4) Supplemental demographic information for each site (sup*.tsv)
- Including ID, age, sex, hand, diagnosis, additional clinical rating scales
(5) MRI protocols (MRI_protocols_{rsMRI, T1w}.tsv)
- Scanning parameters for rs-fMRI and T1w
(6) QC results (group_{bold, T1w}.tsv)
- Outputs of MRIQC for rs-fMRI and T1w
(7) Evaluation of deface quality (deface_QC.tsv)
- Rating scales of quality of defaced T1w
SRPBS_1600 ├── data │ ├── sub-* │ │ ├── rsfmri │ │ ├── t1 │ │ └── fmap │ ... ├── README.txt ├── participants.tsv ├── sup1.tsv ├── sup2.tsv ├── sup3.tsv ├── sup4.tsv ├── sup5.tsv ├── sup6.tsv ├── sup7.tsv ├── sup8.tsv ├── sup9.tsv ├── MRI_protocols_rsMRI.tsv ├── MRI_protocols_T1w.tsv ├── group_bold.tsv ├── group_T1w.tsv └── deface_QC.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 : 91c1cf0529c63e60cdc89112cb2d5743
* As file size is large ( 89.8GB ), 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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