Beat-induced fluctuations in auditory cortical beta-band activity: using EEG to measure age-related changes
Bibliographic record
Abstract
People readily extract regularity in rhythmic auditory patterns, enabling prediction of the onset of the next beat. Recent magnetoencephalography (MEG) research suggests that such prediction is reflected by the entrainment of oscillatory networks in the brain to the tempo of the sequence. In particular, induced beta-band oscillatory activity from auditory cortex decreases after each beat onset and rebounds prior to the onset of the next beat across tempi in a predictive manner. The objective of the present study was to examine the development of such oscillatory activity by comparing electroencephalography (EEG) measures of beta-band fluctuations in 7-year-old children to adults. EEG was recorded while participants listened passively to isochronous tone sequences at three tempi (390, 585, and 780 ms for onset-to-onset interval). In adults, induced power in the high beta-band (20-25 Hz) decreased after each tone onset and rebounded prior to the onset of the next tone across tempo conditions, consistent with MEG findings. In children, a similar pattern was measured in the two slower tempo conditions, but was weaker in the fastest condition. The results indicate that the beta-band timing network works similarly in children, although there are age-related changes in consistency and the tempo range over which it operates.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".