Time courses of cortical beta and gamma-band activity during listening to metronome sounds in different tempi.
Bibliographic record
Abstract
Oscillatory cortical activities in beta-band (13–20 Hz) are related to a somatomotor system, and gamma-bands (20 Hz) are involved with feature binding in perception. Previously gamma-band activity in electroencephalography was found to modulate with musical pulse with a two-beat metric accent. The present study examined beta- and gamma-band activities in auditory cortices recorded via magnetoencephalography (MEG) when subjects listened to musical pulse in various tempi. Tones were presented with intervals of (1) 390 ms, (2) 585 ms, and (3) 780 ms, and (4) with irregular intervals between 390 and 780 ms. In addition, the same tones were presented with a 390-ms interval using a two-beat accent, while occasionally either (5) an accented tone or (6) an unaccented tone was omitted. Beta-band activity decreased immediately after the stimulus and returned to the previous level just before the next stimulus, regardless of the tempo, except in the irregular condition. The tone omission resulted in an extra beta rebound. Gamma-band activity increased right after the pulse or the omission. We propose that beta oscillations may encode the timing of the next sound in a regular pulse sequence, whereas gamma oscillations likely reflect processing of the current auditory events including omissions.
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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".