Overview
The Human Connectome Project – Aging (HCP Aging) dataset aims to characterize brain connectivity patterns and their changes across the lifespan, focusing specifically on aging populations through multimodal neuroimaging and behavioral assessments.
Official Website: humanconnectome.org/study/hcp-lifespan-aging
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: 725 records from 725 unique subjects (1 session per subject)
- T2-weighted scans: 725 records from 725 unique subjects (1 session per subject)
Metadata:
Comprehensive demographic.
Metadata Source Files:
- Subject Info: ndar_subject01.txt (age, sex, race, ethnicity)
- Handedness: edinburgh_hand01.txt (writing hand preference)
- Vitals: vitals01.txt (weight_std, vtl007)
- Sociodemographics: ssaga_cover_demo01.txt (education, income, marital status)
Processed data are organized in a CSV file with the following columns:
| Column Name | Description |
|---|---|
| subjectId | Subject identifier |
| MNI_Warped | Path to MNI warped file |
| MNI_ZSCORE | Path to MNI z-score normalized file |
| MNI_Z_Cropped | Path to MNI z-score cropped file |
| age | Age in years (converted from months) |
| sex | Sex (encoded: 1=Male, 2=Female, 0=Unknown) |
| handedness | Handedness preference (encoded) |
| race | Race category (encoded) |
| ethnicity | Ethnicity (encoded) |
| weight | Weight in kg |
| height | Height |
| education | Education level in years |
| family_income | Annual family income |
| marital_status | Marital status (encoded) |
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, 4 = American Indian/Alaska Native, 5 = Hawaiian/Pacific Islander, 6 = Multiple races.
- Marital Status: 1 = Married, 2 = Never Married/Single, 3 = Divorced, 4 = Widowed, 5 = Living as Married/Cohabiting, 6 = Separated, 0 = Unknown
- Age: 725 subjects (100.0%)
- Sex: 725 subjects (100.0%)
- Weight: 723 subjects (99.7%)
- Height: 724 subjects (99.9%)
- Education: 713 subjects (98.3%)
- Family Income: 534 subjects (73.6%)
- Marital Status: 712 subjects (98.2%)
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: 632 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: March 2025.
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: March 2025
Request Access to HCP Aging Data
To request access to HCP Aging data, please fill out our internal request form. Requests will be reviewed by our data management team.
Citation and Acknowledgment
When using HCP Aging data, please cite the official HCP Aging project and acknowledge the Mind Data Hub preprocessing pipeline:
“Data used in the preparation of this article were obtained from the Human Connectome Project – Aging (HCP Aging) database (humanconnectome.org). The preprocessing and harmonization of data were performed by Mind Data Hub at Stanford University.”
Useful Links