Pleasure in groove is associated with neuromelanin levels in the substantia nigra of younger healthy individuals
Bibliographic record
Abstract
Abstract The pleasurable urge to move in response to music is called groove. Prior research has suggested a potential link between groove and dopamine function. However, no studies to date have directly investigated the relationship between the two. Here, we aimed to assess individual dopamine function in the substantia nigra of healthy individuals using neuromelanin-sensitive magnetic resonance imaging (NM-MRI), a non-invasive method associated with dopamine function, and to investigate the relationship between the individual dopamine proxy index and sensitivity to the groove experience. In this study, 15 younger (< 48 years) and 16 older (≧48 years) healthy individuals participated. Participants listened to ten musical excerpts and rated the groove experience based on “pleasure” and “wanting to move.” To assess whether the groove experience is related to NM levels, type of musical excerpts, and sex, we analyzed with linear mixed-effects regression models. The results showed that higher NM levels ( p = 0.032) and male sex ( p = 0.034) were associated with higher pleasure ratings in the younger group. For the “urge to move” ratings, type of musical excerpts was associated with ratings in both groups ( ps < 0.001), where high-groove music (Janata et al., 2012) receiving higher ratings. Taken together, these results suggest that the “pleasure” aspect of the groove experience in younger individuals was related to dopamine levels in the substantia nigra, but may not be associated with the “urge to move.” Thus, pleasure and the urge to move are likely to involve distinct dopaminergic pathways and mechanisms, warranting further investigation.
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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 | 0.001 | 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".