Musical Anhedonia, timbre, and the rewards of music listening
Bibliographic record
Abstract
Pleasure in music has been linked to predictive coding of melodic and rhythmic patterns, subserved by connectivity between regions in the brain’s auditory and reward networks. Specific musical anhedonics derive little pleasure from music and have altered auditory-reward connectivity, but no difficulties with music perception abilities and no generalized physical anhedonia. Recent research suggests that specific musical anhedonics experience pleasure in nonmusical sounds, suggesting that the implicated brain pathways may be specific to music reward. However, this work used sounds with clear real-world sources (e.g., babies laughing, crowds cheering), so positive hedonic responses could be based on the referents of these sounds rather than the sounds themselves. We presented specific musical anhedonics and matched controls with isolated short pleasing and displeasing synthesized sounds of varying timbres with no clear real-world referents. While the two groups found displeasing sounds equally displeasing, the musical anhedonics gave substantially lower pleasure ratings to the pleasing sounds, indicating that their sonic anhedonia is not limited to musical rhythms and melodies. Furthermore, across a large sample of participants, mean pleasure ratings for pleasing synthesized sounds predicted significant and similar variance in six dimensions of musical reward considered to be relatively independent, suggesting that pleasure in sonic timbres play a role in eliciting reward-related responses to music. We replicate the earlier findings of preserved pleasure ratings for semantically referential sounds in musical anhedonics and find that pleasure ratings of semantic referents, when presented without sounds, correlated with ratings for the sounds themselves. This association was stronger in musical anhedonics than in controls, suggesting the use of semantic knowledge as a compensatory mechanism for affective sound processing. Our results indicate that specific musical anhedonia is not entirely specific to melodic and rhythmic processing, and suggest that timbre merits further research as a source of pleasure in music.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".