Associative memory is more strongly predicted by age-related differences in the prefrontal cortex than medial temporal lobes
Bibliographic record
Abstract
It is well established that episodic memory declines with age and one of the primary explanations for this decline is an age-related impairment in the ability to form new associations. At a neural level, both the medial temporal lobe (MTL) and lateral prefrontal cortex (PFC) are thought to be critical for associative memory, and grey matter volume loss in these regions has been associated with age-related declines in episodic memory. While some recent work has compared the relative contributions of grey matter volume in MTL and PFC regions to item and associative memory, studies investigating the unique and shared contributions of age-related differences in the MTL and PFC to memory differences are still rare. In this study, we use a lifespan approach to examine the relationship between grey matter volume within substructures of the MTL and PFC on the one hand and item and associative memory on the other. To this end, we used data from over 300 healthy individuals uniformly spread across the adult lifespan from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) and tested the multivariate relationship between grey matter volumes and item/associative memory scores using canonical correlation analysis. We show that structures of the PFC alone predict memory performance better than either structures of the MTL alone or PFC and MTL combined. Moreover, our results also indicate that grey matter volume in the inferior frontal gyrus - pars opercularis, superior frontal gyrus, and middle frontal gyrus relates most strongly to memory (particularly associative memory, which loaded higher than item memory) and this effect persists when controlling for age and education. Finally, we also show that the relationship between frontal grey matter volume and memory is not moderated by age or sex. Taken together, these findings emphasize the critical role of the frontal lobes, and the control processes they subserve, in determining the effects of age on associative memory.
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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".