Older Adults’ Lure Discrimination Difficulties on the Mnemonic Similarity Task Are Significantly Correlated With Their Visual Perception
Bibliographic record
Abstract
OBJECTIVES: Pattern separation in memory encoding entails creating and storing distinct, detailed representations to facilitate storage and retrieval. The Mnemonic Similarity Task (MST; Stark, S. M., Yassa, M. A., Lacy, J. W., & Stark, C. E. [2013]. A task to assess behavioral pattern separation [BPS] in humans: Data from healthy aging and mild cognitive impairment. Neuropsychologia, 51, 2442-2449) has been used to argue that normal aging leads to pattern separation decline. We sought to replicate previous reports of age-related difficulty on this behavioral pattern separation estimate and to examine its neuropsychological correlates, specifically long-term memory function, executive function, and visual perception. METHODS: We administered an object version of the MST to 31 young adults and 38 older adults. It involved a single-probe recognition memory test in which some of the originally studied objects had been replaced with perceptually similar lures, and participants had to identify each as old, a lure, or new. RESULTS: Despite their corrected item recognition scores being superior to those of the young adults, the older adults had significantly greater difficulty than the young in discriminating the similar-looking lures from the original items. Interestingly, this lure discrimination difficulty was significantly correlated with visual perception rather than with long-term memory or executive function. DISCUSSION: These results suggest that although adult age differences on the MST are reliable, care should be taken to separate perceptual from memory discrimination difficulties as the reason.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".