Overview
The Parkinson’s Progression Markers Initiative (PPMI) is an observational clinical study designed to identify biomarkers of Parkinson’s Disease (PD) progression through comprehensive imaging, clinical assessments, genetics, and biospecimen collection.
Official Website: ppmi-info.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: 835 records from 356 unique subjects (~2.35 sessions per subject)
- T2-weighted scans: 835 records from 356 unique subjects (~2.35 sessions per subject)
Metadata:
Comprehensive demographic, clinical, and ...
Metadata Source Files:
- Primary Source: diagnosis.csv
- Main data (Age, sex, weight, research_group, visit, study_date, and ...): Demographics_31Jan2025.csv
- Supplementary data (handedness, hispanic, race variables, Education Source, and ...) : Socio-Economics_31Jan2025.csv
- Education Source - Online Socioeconomics: Socioeconomic_Status__Online__31Jan2025.csv
Processed data are organized in a CSV file with the following columns:
| Column Name | Description |
|---|---|
| subjectId | Subject identifier (PATNO) |
| sessionName | Session directory name (date-time format) |
| MNI_Warped | Path to warped MNI file |
| MNI_ZSCORE | Path to z-score normalized file |
| MNI_Z_Cropped | Path to cropped z-score file |
| age | Age in years (e.g., 71.1, 68.9, 55.4) |
| sex | Sex encoded (1=male, 2=female) |
| weight | Weight in kilograms |
| research_group | Research group classification (PD, Control, Prodromal, SWEDD) |
| handedness | Hand dominance (1=right, 2=left, 3=ambidextrous, 0=unknown) |
| Hispanic | Hispanic/Latino ethnicity (1=no, 2=yes, 0=unknown) |
| race_combined | Combined race variable (1=white, 2=black, 3=asian, 6=mixed, 7=other, 0=unknown) |
| education_years | Years of education (range: 10-24 years) |
Encoding Dictionaries:
- Sex: 1 = Male, 2 = Female, 0 = Unknown
- Handedness: 0 = Unknown, 1 = Right, 2 = Left, 3 = Ambidextrous
- Ethnicity: 0 = Unknown, 1 = Non-Hispanic, 2 = Hispanic
- Race: 0 = Unknown, 1 = White, 2 = Black, 3 = Asian, 7 = Other
Research Group Distribution:
- Parkinson's Disease (PD): 542 records (64.9%)
- Healthy Controls (Control): 135 records (16.2%)
- Prodromal Stage: 82 records (9.8%)
- Scan Without Evidence of Dopaminergic Deficit (SWEDD): 76 records (9.1%)
Sex Distribution:
- Male (1): 556 records (66.6%)
- Female (2): 279 records (33.4%)
Education Years Distribution (Top 10):
- 16 years: 205 subjects (most common – Bachelor's degree)
- 18 years: 144 subjects (Master's degree level)
- 12 years: 80 subjects (High school)
- 14 years: 76 subjects (Some college)
- 20 years: 47 subjects (Doctoral level)
- 13 years: 47 subjects
- 15 years: 46 subjects
- 11 years: 39 subjects
- 17 years: 34 subjects
- 19 years: 24 subjects
Download Data Date: May 2025
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: 330 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: July 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
Download Data Date: Sep 2025
Request Access to PPMI Data
To request access to PPMI data, please fill out our internal request form. Requests will be reviewed by our data management team.
Citation and Acknowledgment
When using PPMI data, please cite the official PPMI project and acknowledge the Mind Data Hub preprocessing pipeline:
“Data used in the preparation of this article were obtained from the Parkinson’s Progression Markers Initiative (PPMI) database (ppmi-info.org). The preprocessing and harmonization of data were performed by Mind Data Hub at Stanford University.”
Useful Links