Induced oscillatory signaling in the beta frequency of top-down pain modulation
Bibliographic record
Abstract
Abstract Background: Induced synchronized brain activity, particularly in the beta-frequency range, has rarely been investigated in human electrophysiological studies of attentional modulation of the perception of nociceptive stimuli. Methods: We measured time-resolved brain responses to nociceptive stimuli in healthy subjects (final data set: n = 17) using magnetoencephalography (MEG). In addition to investigating evoked responses as previous studies, we tested whether synchronized beta activity induced by nociceptive stimuli differs between 2 attentional conditions. Subjects were presented simultaneously with 2 stimulus modalities (pain-producing intraepidermal electrical stimuli and visual stimuli) in 2 different experimental conditions, ie, “attention to pain” and “attention to color.” Pain ratings between conditions were compared using a 2-sided paired-samplettest; MEG data were analyzed with Brainstorm. Results: Pain ratings were significantly higher in the “attention to pain” compared with the “attention to color” condition. Peak amplitudes of the evoked responses were significantly larger in the “attention to pain” condition bilaterally in the insula and secondary somatosensory cortex, and in the primary somatosensory cortex (SI) contralateral to stimulation. Induced responses to painful stimuli were significantly stronger in contralateral SI in the beta-frequency range in the “attention to pain” condition. Conclusions: This study replicates previous reports w.r.t. the attentional modulation of evoked responses and suggests a functional role of induced oscillatory activity in the beta frequency in top-down modulation of nociceptive stimuli.
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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".