Overview
The OpenNeuro platform hosts a wide variety of open-access neuroimaging datasets from multiple studies and research projects. From this collection, Mind Data Hub has currently selected and processed only the dataset ds004215 for inclusion in our repository.
Official Website: openneuro.org
Data Available in Mind Data Hub
Below, we summarize the modalities and number of subjects processed and available for request in Mind Data Hub:
Structural MRI (T1-weighted & T2-weighted)
Preprocessing Steps:
- Conversion to NIfTI format (If needed)
- Brain Extraction
- Registration to MNI Space using ANTs (Rigid + Affine transformations)
- Quality Control (QC)
Data Available:
- T1-weighted scans: 183 records from 252 unique subjects
- T2-weighted scans: 182 record sfrom 182 unique subjects
Metadata:
Comprehensive demographic.
Metadata Source Files (1 main file):
- Primary Demographics Source: metadata.csv
| Column Name | Description |
|---|---|
subjectId |
Subject identifier (e.g., sub-ON99943) |
MNI_Warped |
Path to MNI warped brain image |
MNI_ZSCORE |
Path to Z-score normalized brain image |
MNI_Z_Cropped |
Path to Z-score normalized and cropped brain image |
age |
Subject age (string, may contain 'n/a') |
sex |
Encoded sex (0 = n/a, 1 = male, 2 = female) |
handedness |
Encoded handedness (0 = n/a, 1 = right, 2 = left, 3 = ambidextrous) |
Encoding Dictionaries:
- Sex: 1 = Male, 2 = Female, 0 = Unknown
- Handedness: 0 = Unknown, 1 = Right, 2 = Left, 3 = Ambidextrous
Download Data Date: Oct 2024
Functional MRI (Resting-state fMRI)
Preprocessing Steps (fMRIPrep):
- Conversion to NIfTI (BIDS format)
- Slice-timing and motion correction
- Brain extraction and normalization to MNI
- Denoising and smoothing
- Quality Control (QC) and time-series extraction
Data Available:
- fMRI scans processed using fMRIPrep: 219 Subjects.
- Comprehensive QC files.
Dedicated scripts are available for both BIDS conversion and parcellation:
- An automated script converts raw imaging data to the standardized BIDS format. Access BIDS conversion script (GitHub)
- A separate script is provided for parcellation calculations. Access parcellation script (GitHub)
Download Data Date: Oct 2024.
Diffusion Tensor Imaging (DTI)
Preprocessing Steps:
- Convert DICOM to NIfTI
- Topup Correction (Using a top-up tool from FSL)
- Eddy Correction (Using eddy tool from FSL)
- Brain Extraction (Using Bet tool from FSL)
- Merging of Acquisitions (If the session is split into multiple scans)
- DTI Model Fitting(Using the Dtifit tool from FSL)
- Registration to MNI Space using ANTs (Rigid + Affine transformations)
- QC
Data Available:
- fMRI scans processed using fMRIPrep: 238 Subjects.
- Comprehensive QC files.
Download Data Date: Oct 2024
Request Access to OpenNeuro Data
To request access to OpenNeuro data, please fill out our internal request form. Requests will be reviewed by our data management team.
Citation and Acknowledgment
When using OpenNeuro data, please cite the official OpenNeuro project and acknowledge the Mind Data Hub preprocessing pipeline:
“Data used in the preparation of this article were obtained from the OpenNeuro (dataset ds004215) database (openneuro.org). The preprocessing and harmonization of data were performed by Mind Data Hub at Stanford University.”
Useful Links