Melodic Priming of Motor Sequence Performance: The Role of the Dorsal Premotor Cortex
Bibliographic record
Abstract
The purpose of this study was to determine whether exposure to specific auditory sequences leads to the induction of new motor memories and to investigate the role of the dorsal premotor cortex (dPMC) in this crossmodal learning process. Fifty-two young healthy non-musicians were familiarized with the sound to key-press mapping on a computer keyboard and tested on their baseline motor performance. Each participant received subsequently either continuous theta burst stimulation (cTBS) or sham stimulation over the dPMC and was then asked to remember a 12-note melody without moving. For half of the participants, the contour of the melody memorized was congruent to a subsequently performed, but never practiced, finger movement sequence (Congruent group). For the other half, the melody memorized was incongruent to the subsequent finger movement sequence (Incongruent group). Hearing a congruent melody led to significantly faster performance of a motor sequence immediately thereafter compared to hearing an incongruent melody. In addition, cTBS speeded up motor performance in both groups, possibly by relieving motor consolidation from interference by the declarative melody memorization task. Our findings substantiate recent evidence that exposure to a movement-related tone sequence can induce specific, crossmodal encoding of a movement sequence representation. They further suggest that cTBS over the dPMC may enhance early offline procedural motor skill consolidation in cognitive states where motor consolidation would normally be disturbed by concurrent declarative memory processes. These findings may contribute to a better understanding of auditory-motor system interactions and have implications for the development of new motor rehabilitation approaches using sound and non-invasive brain stimulation as neuromodulatory tools.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".