Temporal pole volume is associated with episodic autobiographical memory in healthy older adults
Bibliographic record
Abstract
Recollection of personal past events differs across the lifespan. Older individuals recall fewer episodic details and convey more semantic information than young. Here we examine how gray matter volumes in temporal lobe regions integral to episodic and semantic memory (hippocampus and temporal poles, respectively) are related to age differences in autobiographical recollection. Gray matter volumes were obtained in healthy young (n = 158) and old (n = 105) adults. The temporal pole was demarcated and hippocampus segmented into anterior and posterior regions to test for volume differences between age groups. The Autobiographical Interview was administered to measure episodic and semantic autobiographical memory. Volume associations with episodic and semantic autobiographical memory were then assessed. Brain volumes were smaller for older adults in the posterior hippocampus. Autobiographical memory was less episodic and more semanticized for older versus younger adults. Older adults also showed positive associations between temporal pole volumes and episodic autobiographical recall; in the young, temporal pole volume was positively associated with performance on standard laboratory measures of semantic memory. Exploratory analyses revealed that age-related episodic autobiographical memory associations with anterior hippocampal volumes depended on sex. These findings suggest that age differences in brain structures implicated in episodic and semantic memory may portend reorganization of neural circuits to support autobiographical memory in later life.
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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".