Maturation of Hippocampal Subfields in Young Adulthood and Its Relationship With Cognition
Bibliographic record
Abstract
The hippocampus is a key brain region for memory and cognitive functions, which consists of distinct subregions with different developmental trajectories throughout adolescence. However, trajectories of hippocampal subfield change in young adulthood remain uncharacterized, as is their potential relationship with cortical brain aging and cognitive ability during this time. We conducted two magnetic resonance imaging (MRI) follow-ups of a prenatal birth cohort in young adulthood and studied the effects of chronological age and cortical brain age on the volume of hippocampal subfields in the early 20s (n = 109; 51% men) and late 20s (n = 251; 53% men) and how these age-related volumetric changes might relate to full-scale IQ (FSIQ). We showed that CA1 and CA4DG subfields continue to grow in the third decade of life and that this growth can be observed both at the level of chronological age as well as estimated cortical brain age at both MRI timepoints. Moreover, in men, a larger size of these age-related subfields was associated with higher FSIQ, and the deviations between cortical brain age and chronological age mediated the relationships between right CA1 and FSIQ, as well as right CA4DG and FSIQ. These findings reveal that coordinated patterns of advanced cortical brain aging and hippocampal maturation may confer a cognitive advantage in young adulthood.
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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 | 0.001 | 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".