Overview
The Human Connectome Project – Development (HCP Development) dataset aims to understand brain development and connectivity during adolescence through multimodal neuroimaging and behavioral data.
Official Website: humanconnectome.org/study/hcp-lifespan-development
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: 652 records from 652 unique subjects (1 session per subject)
- T2-weighted scans: 652 records from 652 unique subjects (1 session per subject)
Metadata:
Comprehensive demographic.
Processed data are organized in a CSV file with the following columns:
| Column Name | Description |
|---|---|
subjectId |
Subject identifier (e.g., HCD0001305) |
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 |
Age in years (converted from months) |
sex |
Encoded sex (0=Unknown, 1=Male, 2=Female) |
handedness |
Encoded handedness (0=Unknown, 1=Right, 2=Left, 3=Ambidextrous) |
race |
Encoded race (0=Unknown, 1=White, 2=Black, 3=Asian, 4=Native, 5=Pacific, 6=Multiracial) |
ethnicity |
Encoded ethnicity (0=Unknown, 1=Non-Hispanic, 2=Hispanic) |
weight |
Body weight |
height |
Height |
education |
Background education level |
job |
Job/occupation category |
family_income |
Annual family income |
mother_age |
Mother's age at time of pregnancy |
father_age |
Father's age at time of pregnancy |
birth_country_dad |
Father's birth country |
country_origin |
Country of origin |
father_education |
Father's education level |
mother_education |
Mother's education level |
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.
- Total subjects: 652
- Coverage: 100% for core demographics (age, sex, race, ethnicity, country_origin)
- Variable coverage for socioeconomic variables (23-24% for parent education)
- Age range: 5.6-21.9 years
Download Data Date: March 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: 566 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 Development Data
To request access to HCP Development data, please fill out our internal request form. Requests will be reviewed by our data management team.
Citation and Acknowledgment
When using HCP Development data, please cite the official HCP Development 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 Development) database (humanconnectome.org). The preprocessing and harmonization of data were performed by Mind Data Hub at Stanford University.”
Useful Links