Emotional time travel: the role of emotion in temporal memory
Bibliographic record
Abstract
emotional experiences occurred can be adaptive, yet there is no consensus on how emotion influences temporal aspects of memory. Temporal memory, a type of associative memory, refers to the capacity to encode, store, and retrieve information about the sequence and timing of events. This Special Issue presents evidence on how emotion affects three aspects of temporal memory: temporal-order, temporal source, and event segmentation. The contributions suggest that emotion often increases temporal-order memory, a result that is harder to reconcile with some dominant emotional memory theories, including the Object-Based Framework, the Dual Representation Account or other trade-off models, but may fit with Arousal-Biased Competition theory. The contributions also suggest that emotion can act as a boundary between events, although only under some experimental set-ups. Findings regarding its effect on temporal source memory were less clear. We discuss the diversity of findings in light of theories of emotional associative memory and methodological factors, such as the direction of the shift in emotional experience and discrepancies between temporal-order and temporal distance measures as indices of event boundaries. We provide a roadmap for future studies aimed at understanding how emotion shapes the fate of our memories as they unfold in time.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.013 | 0.020 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".