Temporal context effects are associated with cognitive status in advanced age
Bibliographic record
Abstract
The perception of temporal intervals changes during the life-span, and especially older adults demonstrate specific impairments of timing abilities. Recently, we demonstrated that timing performance and cognitive status are correlated in older adults, suggesting that timing tasks can serve as a behavioral marker for the development of dementia. Easy-to-administer and retest-capable timing tasks therefore have potential as diagnostic tools for tracking cognitive decline. However, before being tested in a clinical cohort study, a further validation and specification of the original findings is warranted. Here we introduce several modifications of the original task and investigated the effects of temporal context on time perception in older adults (> 65 years) with low versus high scores in the Montreal Cognitive Assessment survey (MoCA) and a test of memory functioning. In line with our previous work, we found that temporal context effects were more pronounced with increasing memory deficits, but also that these effects are stronger for realistic compared to abstract visual stimuli. Furthermore, we show that two distinct temporal contexts influence timing behavior in separate experimental blocks, as well as in a mixed block in which both contexts are presented together. These results replicate and extend our previous findings. They demonstrate the stability of the effect for different stimulus material and show that timing tasks can reveal valuable information about the cognitive status of older adults. In the future, these findings could serve as a basis for the development of a diagnostic tool for pathological cognitive decline at an early, pre-clinical stage.
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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 | 0.003 |
| 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) | 0.002 | 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".