The effect of modality and order presentation of emotional stimuli on time perception
Bibliographic record
Abstract
Despite human accuracy in perceiving time, many factors can modulate the subjective experience of time. For example, it is widely reported that emotion can expand or shrink our perception of time and that temporal intervals are perceived as longer when marked by auditory stimuli than by visual stimuli. In the present study, we aimed at investigating whether the influence of emotion on time perception can be altered by the order in which emotional stimuli are presented and the sensory modality in which they are presented. Participants were asked to complete a time bisection task in which emotional stimuli were presented either acoustically or visually, and either before or after interval to be estimated. We observed a main effect of modality (longer perceived duration and lower variability in the auditory than in the visual modality) as well as a main effect of emotion (temporal overestimation for negative stimuli compared to neutral). Importantly, the effects of modality and emotion interacted with the order of presentation of the emotional stimuli. In the visual condition, when emotional stimuli were presented after the temporal intervals, participants overestimated time, but no differences between negative and neutral stimuli were observed when emotional stimuli were presented first. In the auditory condition, no significant effect of emotion on perceived duration was found. Results suggest that negative emotions affect our perception of durations acting at the decision-making stage rather than at the pacemaker one. No effect on time perception was observed for emotional auditory stimuli.
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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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".