Overview
The Australian Imaging, Biomarkers & Lifestyle (AIBL) Study of Ageing is a longitudinal research initiative aimed at identifying biomarkers, imaging markers, and lifestyle factors that influence the development and progression of Alzheimer’s disease and other forms of dementia. The study includes neuroimaging, cognitive assessments, blood biomarkers, and lifestyle data from older adults, including both healthy controls and individuals with mild cognitive impairment (MCI) or Alzheimer’s disease (AD).
Official Website: aibl.csiro.au
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: 1,293 records from 692 unique subjects
- T2-weighted scans: 611 records from 692 unique subjects
Metadata:
Comprehensive demographic.
Metadata Source Files:
aibl_ptdemog_01-Jun-2018.csv— Demographics (862 records)aibl_medhist_01-Jun-2018.csv— Medical history (smoking, conditions)aibl_pdxconv_01-Jun-2018.csv— Diagnosis (1,688 records)idaSearch_4_02_2025.csv— Accurate ages per sessionaibl_mri3meta_01-Jun-2018.csv— MRI visit dates/protocolsaibl_mrimeta_01-Jun-2018.csv— Secondary MRI metadataall_subjects_qc_results.csv— QC scores
| Column Name | Description |
|---|---|
| subjectId | Subject identifier (RID) |
| sessionName | Session directory name (YYYY-MM-DD_HH_MM_SS.S format) |
| MNI_Warped | Path to MNI warped brain file |
| MNI_ZSCORE | Path to z-score normalized file |
| MNI_Z_Cropped | Path to cropped z-score file |
| age | Age in years (61–103, mean: 80.7±7.1) |
| sex | Sex encoded (1=Male, 2=Female) |
| smoking_history | Smoking history (0=No, 1=Yes, -1=Unknown) |
| current_diagnosis | Current diagnosis (Normal, MCI, AD, Unknown) |
| scanner_manufacturer | Scanner manufacturer (Philips, GE, Siemens, Unknown) |
| Overall_qc_score | SynthSeg QC score (0–1 scale, session-type specific) |
Encoding Dictionaries:
- Sex: 1 = Male, 2 = Female
- Smoking History: 0 = No, 1 = Yes, -1 = Unknown
- Diagnosis: Normal, MCI, AD, Unknown
Diagnosis Distribution (T1):
- Normal: 976 (75.4%)
- MCI: 195 (15.1%)
- AD: 119 (9.2%)
- Unknown: 3 (0.3%)
Diagnosis Distribution (T2):
- Normal: 471 (77.1%)
- MCI: 92 (15.1%)
- AD: 46 (7.5%)
- Unknown: 2 (0.3%)
Sex Distribution:
- Female: 470 (54.5%)
- Male: 392 (45.5%)
Scanner Manufacturer Distribution:
- Unknown: ~65.6% of scans
- Philips: ~60.8% of known scans
- GE: ~5.1% of known scans
Download Data Date: May 2025
Functional MRI (Resting-state fMRI)
AIBL does not have enough FMRI subjects!
Diffusion Tensor Imaging (DTI)
AIBL does not have enough DTI subjects!
Request Access to AIBL Data
To request access to AIBL data, please fill out our internal request form. Requests will be reviewed by our data management team.
Citation and Acknowledgment
When using AIBL data, please cite the official AIBL project and acknowledge the Mind Data Hub preprocessing pipeline:
“Data used in the preparation of this article were obtained from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) database (aibl.csiro.aug). The preprocessing and harmonization of data were performed by Mind Data Hub at Stanford University.”
Useful Links