Enhancement of Neuroplastic P2 and N1c Auditory Evoked Potentials in Musicians
Bibliographic record
Abstract
P2 and N1c components of the auditory evoked potential (AEP) have been shown to be sensitive to remodeling of the auditory cortex by training at pitch discrimination in nonmusician subjects. Here, we investigated whether these neuroplastic components of the AEP are enhanced in musicians in accordance with their musical training histories. Highly skilled violinists and pianists and nonmusician controls listened under conditions of passive attention to violin tones, piano tones, and pure tones matched in fundamental frequency to the musical tones. Compared with nonmusician controls, both musician groups evidenced larger N1c (latency, 138 msec) and P2 (latency, 185 msec) responses to the three types of tonal stimuli. As in training studies with nonmusicians, N1c enhancement was expressed preferentially in the right hemisphere, where auditory neurons may be specialized for processing of spectral pitch. Equivalent current dipoles fitted to the N1c and P2 field patterns localized to spatially differentiable regions of the secondary auditory cortex, in agreement with previous findings. These results suggest that the tuning properties of neurons are modified in distributed regions of the auditory cortex in accordance with the acoustic training history (musical- or laboratory-based) of the subject. Enhanced P2 and N1c responses in musicians need not be considered genetic or prenatal markers for musical skill.
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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 | 0.000 | 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) | 0.003 | 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".