Age and Gender Predict Volume Decline in the Anterior and Posterior Hippocampus in Early Adulthood
Bibliographic record
Abstract
Magnetic Resonance Imaging (MRI) provides a noninvasive method for investigating brain morphology. Within the medial temporal lobe, special attention has been paid to the hippocampus (HC) and amygdala (AG) because of their role in memory, depression, emotion, and learning. Volume changes in these areas have been observed in conjunction with certain disease states, e.g. Alzheimer's disease, post-traumatic stress disorder, and depression. Aging has also been shown to result in gray matter volume loss of the overall brain, including the HC. With regard to gender specificity, results suggest a larger shrinkage for men of brain gray matter, with controversial observations being made for the HC. With recently refined MRI acquisition and segmentation protocols, the HC and AG of 80 subjects in early adulthood (39 men and 41 women, age 18-42 years) were investigated. Whereas the volume of the AG appeared to be independent of age and gender, a significant negative correlation with age for both left and right HC was found in men (r = -0.47 and -0.44, respectively) but not in women (r = 0.01 and 0.02, respectively). The volume decline in men appeared to be linear, starting at the beginning of the third life decade and approximating 1.5% per annum. Using voxel-based regressional analysis, it was shown that changes with age occurred mostly in the head and tail of the HC. This finding underscores the need to include sociodemographic variables in functional and anatomical MRI designs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".