Auditory N1 reveals planning and monitoring processes during music performance
Bibliographic record
Abstract
The current study investigated the relationship between planning processes and feedback monitoring during music performance, a complex task in which performers prepare upcoming events while monitoring their sensory outcomes. Theories of action planning in auditory-motor production tasks propose that the planning of future events co-occurs with the perception of auditory feedback. This study investigated the neural correlates of planning and feedback monitoring by manipulating the contents of auditory feedback during music performance. Pianists memorized and performed melodies at a cued tempo in a synchronization-continuation task while the EEG was recorded. During performance, auditory feedback associated with single melody tones was occasionally substituted with tones corresponding to future (next), present (current), or past (previous) melody tones. Only future-oriented altered feedback disrupted behavior: Future-oriented feedback caused pianists to slow down on the subsequent tone more than past-oriented feedback, and amplitudes of the auditory N1 potential elicited by the tone immediately following the altered feedback were larger for future-oriented than for past-oriented or noncontextual (unrelated) altered feedback; larger N1 amplitudes were associated with greater slowing following altered feedback in the future condition only. Feedback-related negativities were elicited in all altered feedback conditions. In sum, behavioral and neural evidence suggests that future-oriented feedback disrupts performance more than past-oriented feedback, consistent with planning theories that posit similarity-based interference between feedback and planning contents. Neural sensory processing of auditory feedback, reflected in the N1 ERP, may serve as a marker for temporal disruption caused by altered auditory feedback in auditory-motor production tasks.
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 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 | 0.000 | 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) | 0.001 | 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".