Effect of pain on deafferentation-induced modulation of somatosensory evoked potentials
Bibliographic record
Abstract
There is a large body of evidence showing substantial sensorimotor reorganizations after an amputation. These reorganizations are believed to contribute to the development of phantom limb pain, but alternatively, pain might influence the plasticity triggered by the deafferentation. The aim of this study was to test whether pain impacts on deafferentation-induced plasticity in the somatosensory pathways. Fifteen healthy subjects participated in 2 experimental sessions (Pain, No Pain) in which somatosensory evoked potentials (SSEPs) associated with electrical stimulation of the ulnar nerve were assessed before and after temporary ischemic deafferentation induced by inflation of a cuff around the wrist. In the Pain session capsaicin cream was applied on the dorsum of the hand 30 minutes prior to cuff inflation. Results show that pain decreased the amplitude of the N20 (main effect of condition, p = 0.033), with a similar trend for the P25. Temporary ischemic deafferentation had a significant effect on SSEPs (main effect of time), with an increase in the P25 (p = 0.013) and the P45 amplitude (p = 0.005), together with a reduction of the P90 amplitude (p = 0.002). Finally, a significant time x condition interaction, reflecting state-dependent plasticity, was found for the P90 only, the presence of pain decreasing the reduction of amplitude observed in response to deafferentation. In conclusion, these results show that nociceptive input can influence the plasticity induced by a deafferentation, which could be a contributing factor in the cortical somatosensory reorganization observed in chronic pain populations.
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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) | 0.001 | 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".