Dopamine dysregulation in Parkinson’s disease flattens the pleasurable urge to move to musical rhythms
Bibliographic record
Abstract
Abstract The pleasurable urge to move to music (PLUMM) elicits activity in motor and reward areas of the brain and is thought to be driven by predictive processes. Dopamine within motor and limbic cortico-striatal networks is implicated in the predictive processes underlying beat-based timing and music-induced pleasure, respectively. This suggests a central role of cortico-striatal dopamine in PLUMM. This study tested this hypothesis by comparing PLUMM in Parkinson’s disease patients, healthy age-matched, and young controls. Participants listened to musical sequences with varying rhythmic and harmonic complexity (low, medium, high), and rated their experienced pleasure and urge to move to the rhythm. In line with previous results, healthy younger participants showed an inverted U-shaped relation between rhythmic complexity and ratings, with a preference for medium complexity rhythms, while age-matched controls showed a similar, but weaker, inverted U-shaped response. Conversely, PD patients showed a significantly flattened response for both the urge to move and pleasure. Crucially, this flattened response could not be attributed to differences in rhythm discrimination and did not reflect an overall decrease in ratings. Together, these results support the role of dopamine within cortico-striatal networks in the predictive processes that form the link between the perceptual processing of rhythmic patterns, and the affective and motor responses to rhythmic 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 | 0.001 |
| 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".