Olfaction and declarative memory in aging: a meta-analysis
Bibliographic record
Abstract
Olfactory and declarative memory performances are associated, as both functions are processed by overlapping medial-temporal and prefrontal structures and decline in older adults. While a decline in olfactory identification may be related to a decline in declarative memory, the relationship between olfactory detection threshold and declarative memory remains unclear. In this meta-analysis, we assessed (i) the relationship between olfactory identification/detection threshold and verbal declarative memory in cognitively normal older adults, and (ii) the effect of age on these relationships. We included articles from PsychNet, PubMed, and Academic Search Complete according to the following criteria: (i) inclusion of cognitively normal older adults; (ii) assessment of episodic or semantic memory; and (iii) assessment of olfactory identification or detection threshold. Seventeen studies and 22 effect sizes were eligible and included in this meta-analysis. Olfactory identification was associated with episodic (small effect size: r = 0.19; k = 22) and semantic memory (small effect size: r = 0.16; k = 23). Similarly, the olfactory detection threshold was associated with both episodic (small to medium effect size: r = 0.25; k = 5) and semantic memory (small effect size: r = 0.17; k = 7). Age was found to moderate the relationship between olfactory detection threshold and memory performance. Both olfactory identification and detection threshold performances are associated with declarative memory in older adults, and age only moderates the relationship between olfactory detection threshold and declarative memory performances.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.030 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".