Microstructural maturation of the adult mouse brain
Bibliographic record
Abstract
While lifespan studies have consistently shown changes in diffusion MRI (dMRI) metrics indicating gradual microstructural remodeling until middle age, the cellular sources remain unclear due to the lack of microstructural specificity of traditional dMRI measurements. To provide insight into the biophysical mechanisms of dMRI changes during aging, we employ advanced techniques with improved microstructural specificity to study healthy mouse brain maturation from 3-8 months of age. Agreeing with past studies, fractional anisotropy, diffusional kurtosis and myelin-specific MRI metrics increased with age. Our main finding is that kurtosis increases were driven by increases in its sub-component of "isotropic kurtosis" (sensitive to variance of compartmental mean diffusivities), while the remaining sub-component of "anisotropic kurtosis" (sensitive to microstructural anisotropy) remained stable. These observations were accompanied by increases in myelin content and oligodendrocyte density. Our findings suggest that diffusional kurtosis increases during adult mouse brain maturation are not driven by changes in anisotropic structures like axons, but by overall heterogeneity increases that are due, at least in part, to changing oligodendrocyte populations. This work gives further insight into microstructural changes occurring during brain maturation and new insight into the biological underpinnings of dMRI contrast.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".