Positive emotion enhances association-memory.
Bibliographic record
Abstract
The influence of emotion on association-memory is often attributed to arousal, but negative stimuli are typically used to test for these effects. While prior studies of negative emotion on association-memory have found impairments, theories suggest that positive emotion may have a distinct effect on memory, and may lead to enhanced association-memory. Here we tested participants' memory for pairs of positive and neutral words using cued recall, supplemented with a mathematical modeling approach designed to disentangle item- versus association-memory effects that may otherwise confound cued-recall performance. In our main experiment, as well as in additional supplemental experiments, we consistently found enhanced association-memory due to positive emotion. Interestingly, we observed enhanced association-memory in pairs composed of two positive words, but not in pairings of one positive and one neutral word, indicating that this enhancement may only when a sufficient amount of positive emotion is present. These results provide further evidence that positive information is processed differently than negative and that, when examining association formation, valence as well as arousal must be considered. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".