Cortical oscillations are modified by expertise in dance and music: Evidence from live dance audience
Bibliographic record
Abstract
Over the past decades, the focus of brain research has expanded from using strictly controlled stimuli towards understanding brain functioning in complex naturalistic contexts. Interest has increased in measuring brain processes in natural interaction, including classrooms, theatres, concerts and museums to understand the brain functions in the real world. Here, we examined how watching a live dance performance with music in a real-world dance performance setting engages the brains of the spectators. Expertise in dance or music has been shown to modify brain functions, including when watching dance or listening to music. Therefore, we recorded electroencephalography (EEG) from an audience of dancers, musicians and novices as they watched the live dance performance and analysed their cortical oscillations. We compared intrabrain oscillations when participants watched the performance (with music) or listened to the music alone without the dance. We found that dancers have stronger fronto-central and parieto-occipital theta phase synchrony (4-8 Hz) than novices when watching dance, likely reflecting the effects of dance experience on motor imagery, multisensory and social interaction processes. Also, compared with novices, dancers had stronger delta phase synchrony (0.5-4 Hz) when listening to music, and musicians had stronger delta phase synchrony when watching dance, suggesting expertise in music and dance enhances sensitivity or attention to temporal regularities in movement and sound.
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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 | 0.000 | 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".