Inhibitory effects of heterotopic noxious counter‐stimulation on perception and brain activity related to Aβ‐fibre activation
Bibliographic record
Abstract
Heterotopic noxious counter-stimulation (HNCS) inhibits pain and pain processes through cerebral and cerebrospinal mechanisms. However, it is unclear whether HNCS inhibits non-nociceptive processes, which needs to be clarified for a better understanding of HNCS analgesia. The aim of this study was to examine the effects of HNCS on perception and scalp somatosensory evoked potentials (SEPs). Seventeen healthy volunteers participated in two counter-balanced sessions, including non-nociceptive (selective Aβ-fibre activation) or nociceptive electrical stimulation, combined with HNCS. HNCS was produced by a 20-min cold pressor test (left hand) adjusted individually to produce moderate pain (mean ± SEM: 42.5 ± 5.3 on a 0-100 scale, where 0 is no pain and 100 the worst pain imaginable). Non-nociceptive electrical stimulation was adjusted individually at 80% of pain threshold and produced a tactile sensation in every subject. Nociceptive electrical stimulation was adjusted individually at 120% of RIII-reflex threshold and produced moderate pain (45.3 ± 4.5). Shock sensation was significantly decreased by HNCS compared with baseline for non-nociceptive (P < 0.001) and nociceptive (P < 0.001) stimulation. SEP peak-to-peak amplitude at Cz was significantly decreased by HNCS for non-nociceptive (P < 0.01) and nociceptive (P < 0.05) stimulation. These results indicate that perception and brain activity related to Aβ-fibre activation are inhibited by HNCS. The mechanisms of this effect remain to be investigated to clarify whether it involves inhibition of spinal wide-dynamic-range neurons by diffuse noxious inhibitory controls, supraspinal processes or both.
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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 | 0.000 |
| 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) | 0.002 | 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".