A Neural Mechanism Underlying Memory Failure in Older Adults
Bibliographic record
Abstract
Older adults have reduced memory, primarily for recall, but also for recognition (Craik and McDowd, 1987), particularly for unfamiliar faces (Bartlett et al., 1989). Behavioral studies have shown that age-related memory declines are due in part to distraction from impaired inhibition of task-irrelevant input during encoding (Healey et al., 2008). Functional magnetic resonance imaging (fMRI) has been used to uncover the sources of memory deficits associated with aging. To date, this work has focused on successful encoding, while the neural correlates of unsuccessful encoding are unknown. Here, we provide novel evidence of a neural mechanism underlying memory failures exclusively affecting older adults. Whereas both younger and older adults showed reduced activation of brain regions important for encoding (e.g., hippocampus) during unsuccessful encoding, only older adults showed increased activity in brain regions mediating distraction (e.g., auditory cortex) and in left prefrontal cortex. Further, these regions were functionally connected with medial parietal areas, previously identified as default mode regions (Raichle and Snyder, 2007), which may reflect environmental monitoring. Our results suggest that increased distraction from task-irrelevant input (auditory in this case), associated with the unfamiliar and noisy fMRI environment, may increase environmental monitoring. This in turn could hinder suppression of default mode processing, resulting in memory failures in older adults. These findings provide novel evidence of a brain mechanism underlying the behavioral evidence that impaired inhibition of extraneous input during encoding leads to memory failure in older adults and may have implications for the ubiquitous use of fMRI for investigating neurocognitive aging.
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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 | 0.001 | 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".