Auditory-motor integration in music performance, learning, and memory
Bibliographic record
Abstract
Auditory-motor skills such as speaking or playing a musical instrument require skill in processing auditory outcomes and performing actions that produce those outcomes. A growing body of evidence suggests that perception and production components of auditory-motor skill are integrated by reciprocal auditory-to-motor and motor-to-auditory interactions. Much remains unknown about how complex auditory sequences map to complex movement sequences such as those required of speech or music performance. Less still is known about how auditory-motor interactions influence the way skilled performers learn and remember novel auditory-motor sequences. The research described in this thesis examined these questions in the context of music performance. Music performance is a common and complex auditory-motor behavior that presents a useful model for examining human auditory-motor capabilities as it requires precise control of both pitch and temporal sequences of events. Three studies examined how auditory-motor interactions influence the way skilled musicians map pitch and temporal sequences to movements and the way musicians learn and remember music. The first study examined how auditory pitch and temporal sequence structure in music engage motor neural networks in auditory-motor interactions (Chapter 2). This study revealed motor networks that are sensitive to both pitch and temporal structure when musicians listen to and subsequently perform music. This finding suggests that the motor system integrates multiple dimensions of auditory sequence structure when performers map auditory sequences to motor sequences. The second study examined how performers use auditory and motor information to learn auditory sequences (Chapter 3). This study revealed that musicians better recognize auditory sequences that they hadlearned while producing them with auditory feedback than while hearing them only, indicating that motor learning facilitates subsequent auditory memory for skilled performers. The third study examined how individual differences in auditory and motor imagery abilities influence the way musicians learn novel music and subsequently remember that music (Chapter 4). This study revealed that auditory imagery abilities help performers learn novel music by compensating for missing sound and reducing sensitivity to interfering information; auditory imagery abilities also help performers recall music during performance with greater temporal regularity. Overall, these results suggest that auditory imagery abilities aid learning and subsequent recall of music differently. Together, these studies illuminate how auditory-motor integration functions in skilled performance and how it contributes to auditory-motor sequence learning and memory.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".