Body maps of the sensation of musical groove
Bibliographic record
Abstract
Rhythmic music often leads to an urge to move the body in time with the music. This urge to move can be a pleasurable experience. In psychology, we define the pleasurable wanting to move to music as groove. Here, we investigate where in the body these two groove components-movement and pleasure-are felt and whether the embodied sensations depend on the musical genre. Using a body sensation map paradigm, we found that the funk genre, which elicited high levels of groove, increased sensations across the whole body, including in the head, shoulders, upper chest, abdomen, arms, hands, hips, legs, and feet. Importantly, wanting to move and pleasure produced distinct body maps, with wanting to move associated with more sensation in the extremities and pleasure more associated with feelings in the chest and abdomen. Exploratory analyses also found an inverted U-shaped relationship between wanting to move and pleasure ratings and the rhythmic complexity of the excerpts, as indexed by pulse entropy, and that medium pulse entropy produced sensations in the upper chest, shoulders, hips, and ankles. The results are discussed in relation to theories of embodied predictive processing, highlighting the potential role of interoception in musical prediction and reward. Overall, our study shows clear patterns of embodied differentiation for different components and levels of groove.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".