Older adults can use memory for distinctive objects, but not distinctive scenes, to rescue associative memory deficits
Bibliographic record
Abstract
Associative memory deficits in aging are frequently characterized by false recognition of novel stimulus associations, particularly when stimuli are similar. Introducing distinctive stimuli, therefore, can help guide item differentiation in memory and can further our understanding of how age-related brain changes impact behavior. How older adults use different types of distinctive information to distinguish overlapping events in memory and to avoid false associative recognition is still unknown. To test this, we manipulated the distinctiveness of items from two stimulus categories, scenes and objects, across three conditions: (1) distinct scenes paired with similar objects, (2) similar scenes paired with distinct objects, and (3) similar scenes paired with similar objects. Young and older adults studied scene-object pairs and then made both remember/know judgments toward single items as well as associative memory judgments to old and novel scene-object pairs ("Were these paired together?"). Older adults showed intact single item recognition of scenes and objects, regardless of whether those objects and scenes were similar or distinct. In contrast, relative to younger adults, older adults showed elevated false recognition for scene-object pairs, even when the scenes were distinct. These age-related associative memory deficits, however, disappeared if the pair contained an object that was visually distinct. In line with neural evidence that hippocampal functioning and scene processing decline with age, these results suggest that older adults can rely on memory for distinct objects, but not for distinct scenes, to distinguish between memories with overlapping features.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".