Age-Related Changes in Diffusion Tensor Imaging Metrics of Fornix Subregions in Healthy Humans
Bibliographic record
Abstract
OBJECTIVE: White matter diffusivity measures of the fornix change with aging, which likely relates to changes in memory and cognition in older adults. Subregional variations in forniceal diffusivity may exist, given its heterogeneous anatomy and connectivity; however, these have not been closely examined in vivo. We examined diffusivity parameters (fractional anisotropy, FA; radial diffusivity, RD; axial diffusivity, AD) in forniceal subregions of healthy subjects and correlated them with age and hippocampal volume. METHODS: Diffusion-weighted imaging and streamline tractography of the fornix were performed on 20 healthy, right-handed females (23-66 years). Six anatomical subregions were defined: midline (body, column, precommissural fornix) or lateral (fimbria, crura, postcommissural fornix). Regression analysis was performed comparing diffusivities against age. Hippocampal and ventricular volumes were also compared. RESULTS: Diffusivity values revealed statistical changes with age in both midline and lateralized subregions. The fornix body and left crus showed age-related alterations in all metrics (FA, RD, AD), whereas only right crus FA was altered. There was no significant change in hippocampal volumes, suggesting that forniceal changes may precede hippocampal age-related changes. CONCLUSIONS: Age-related changes in fornix diffusivity measures appear subregion dependent and asymmetrical. Specific subregion diffusivity measures may be a more sensitive aging marker than hippocampal volume change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".