Familiarity mediates the relationship between emotional arousal and pleasure during music listening
Bibliographic record
Abstract
Emotional arousal appears to be a major contributing factor to the pleasure that listeners experience in response to music. Accordingly, a strong positive correlation between self-reported pleasure and electrodermal activity (EDA), an objective indicator of emotional arousal, has been demonstrated when individuals listen to familiar music. However, it is not yet known to what extent familiarity contributes to this relationship. In particular, as listening to familiar music involves expectations and predictions over time based on veridical knowledge of the piece, it could be that such memory factors plays a major role. Here, we tested such a contribution by using musical stimuli entirely unfamiliar to listeners. In a second experiment we repeated the novel music to experimentally establish a sense of familiarity. We aimed to determine whether (1) pleasure and emotional arousal would continue to correlate when listeners have no explicit knowledge of how the tones will unfold, and (2) whether this could be enhanced by experimentally-induced familiarity. In the first experiment, we presented 33 listeners with 70 unfamiliar musical excerpts in two sessions. There was no relationship between the degree of experienced pleasure and emotional arousal as measured by EDA. In the second experiment, 7 participants listened to 35 unfamiliar excerpts over two sessions separated by 30 min. Repeated exposure significantly increased EDA, even though individuals did not explicitly recall having heard all the pieces before. Furthermore, increases in self-reported familiarity significantly enhanced experienced pleasure and there was a general, though not significant, increase in EDA. These results suggest that some level of expectation and predictability mediated by prior exposure to a given piece of music play an important role in the experience of emotional arousal in response to music.
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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 | 0.004 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".