Holding On to the Past: Older Adults Show Lingering Neural Activation of No-Longer-Relevant Items in Working Memory
Bibliographic record
Abstract
Goal-relevant information can be maintained in working memory over a brief delay interval to guide an upcoming decision. There is also evidence suggesting the existence of a complementary process: namely, the ability to suppress information that is no longer relevant to ongoing task goals. Moreover, this ability to suppress or inhibit irrelevant information appears to decline with age. In this study, we compared younger and older adults undergoing fMRI on a working memory task designed to address whether the modulation of neural representations of relevant and no-longer-relevant items during a delay interval is related to age and overall task performance. Following from the theoretical predictions of the inhibitory deficit hypothesis of aging, we hypothesized that older adults would show higher activation of no-longer-relevant items during a retention delay compared to young adults and that higher activation of these no-longer-relevant items would predict worse recognition memory accuracy for relevant items. Our results support this prediction and more generally demonstrate the importance of goal-driven modulation of neural activity in successful working memory maintenance. Furthermore, we showed that the largest age differences in the regulation of category-specific pattern activity during working memory maintenance were seen throughout the medial temporal lobe and prominently in the hippocampus, further establishing the importance of "long-term memory" retrieval mechanisms in the context of high-load working memory tasks that place large demands on attentional selection mechanisms.
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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) | 0.002 | 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".