Psychophysiological evidence for the role of emotion in adaptive memory.
Bibliographic record
Abstract
Studies demonstrating a mnemonic benefit for encoding words in a survival scenario have revived interest in how human memory is shaped by evolutionary pressures. Prior work on the survival-processing advantage has largely examined cognitive factors as potential proximate mechanisms. The current study, by contrast, focused on the role of perceived threat. Guided by the idea that a survival scenario implies threat, we combined measures of heart rate (HR) with affective ratings to probe the potential presence of fear bradycardia as a marker of freezing--a parasympathetically dominated HR deceleration that reflects the initial stage of the defensive engagement. We replicated the mnemonic advantage in behavior and found that the survival scenario was rated higher in perceived negative arousal than a commonly used control scenario. Critically, words encountered in the survival scenario were associated with more extensive HR deceleration, and this effect was directly related to subsequent recall performance. Our findings point to a role for the involvement of neurobiological fear responses in producing the survival processing advantage, as well as potential links between autonomic changes and cognitive processing in adaptive memory.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".