Do nociceptive stimulation intensity and temporal predictability influence pain-induced corticospinal excitability modulation?
Bibliographic record
Abstract
Temporal predictability and intensity of an impending nociceptive input both shape pain experience and modulate laser-evoked potentials (LEPs) amplitude. However, it remains unclear whether and how these two factors could influence pain-induced corticospinal excitability modulation. The current study investigated the influence of nociceptive stimulation intensity and temporal predictability on motor-evoked potentials (MEPs) modulation, in parallel to their effect on pain perception and LEPs amplitude. Twenty participants completed electroencephalographic and transcranial magnetic stimulation experiments during which two laser nociceptive stimulation intensities (high and low) were either unpredictably delivered (random delay) or preceded by a fixed-timing cue (fixed delay). The amplitude of the conditioned MEPs was significantly reduced only for the high nociceptive stimulation and was not affected by the temporal predictability of pain (despite the fact that temporal predictability modulated the amplitude of P2 LEP component amplitude). However, a posteriori analyses based on patterns of pain-induced MEPs modulation revealed that participants in which nociceptive stimulation resulted in an increase in corticospinal excitability were more affected by the predictability of pain (i.e. increasing corticospinal excitability even more when pain occurrence was predictable), regardless of the nociceptive stimulation intensity; whereas participants in which nociceptive stimulation resulted in a decrease in corticospinal excitability were sensitive to the intensity of the stimulation but not its predictability. These results suggest a potential influence of cognitive factors such as temporal predictability on the response of the motor system in the presence of pain for some participants, contributing to explain, at least in part, the high variability highlighted in a number of previous studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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".