“Tuning in” the Developing Brain: Neurocognitive Effects of Ensemble Music Training on Children
Bibliographic record
Abstract
The ability to self-regulate has been associated with school-readiness and academic achievement. Research has indicated that young children receiving music instruction perform significantly better on self-regulation tasks. The current study assessed the cognitive neurocorrelates of executive attention using event-related potentials (ERPs) as children between the ages of 9-12 years with and without training in a social music program, OrKidstra, completed an auditory Go/NoGo task involving pure tones at 1100Hz and 2000Hz. Preliminary findings indicate that participating in the OrKidstra program decreases children’s reaction times to Go stimuli at 2000Hz and increases the early brain’s response to this tone within individuals (2000Hz vs. 1100Hz in the same children) and between groups (OrKidstra children vs. comparison children). Children also completed the Peabody Picture Vocabulary Test, Fourth Edition (PPVT-IV) to allow us to determine the influence of music learning on verbal comprehension. Family demographics and wellbeing were collected through questionnaires completed by the child’s guardian. Findings from our research may have implications for music training interventions and music training implementation in the school setting, especially as applied to socioeconomically disadvantaged children.
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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) | 0.001 | 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".