Developing and validating an elderly brain template: A comprehensive comparison with MNI152 for age-specific neuroimaging analyses
Bibliographic record
Abstract
• An elderly MRI template was built from 90 OASIS-1 scans matched to 2020 census data. • The template was validated on 282 IXI scans and compared with the MNI152 template. • It showed higher CC and lower MSE after age 60, reflecting brain atrophy patterns. • Dice scores improved by 1–4 % in the caudate, thalamus, hippocampus, and amygdala. • The template and code are available on GitHub/Zenodo for reproducible research. The Montreal Neurological Institute 152 (MNI152) brain template, constructed from young adult brains, may not accurately represent older age–specific morphological changes. Accordingly, we developed and validated the new Elderly template. MRI scans from 90 OASIS-1 participants, matching Japanese census demographics, were used to construct the Elderly template. Spatial normalization accuracy was compared with that of the MNI152 in the IXI dataset. Following UK Biobank–based intracranial volume quality control (±2 SD; 1232–1850 mL), 282 of 313 scans from individuals aged 20–80+ years were included. Whole-brain similarity was assessed with cross-correlation (CC), mean-squared error (MSE), and 3D structural similarity index measure (3D-SSIM). Dice coefficients were computed for white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), and seven subcortical regions. Generalized linear models were used to test the Age × Template interactions (β₃). Significant Age × Template interactions were observed for CC and MSE ( p < 0.001); 3D-SSIM showed a positive but non-significant trend. Dice analyses mirrored this pattern: WM and GM showed minor differences between templates, and the Dice coefficient was parallel. CSF showed a sharp difference at the age ≥60 years. The largest interaction effects (≈1–4 % gain) occurred in the caudate, thalamus, hippocampus, and amygdala, whereas the brainstem, pallidum, and putamen showed minimal differences between templates. The Elderly template more accurately reflects older age–specific morphological changes and enhances spatial normalization accuracy, compared with the MNI152 template. This improvement suggests advancements in age-specific analyses and neurodegenerative disease research, enabling clinical applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".