Cortical evoked responses to evaluate the effect of spinal cord stimulation on the pain pathways
Bibliographic record
Abstract
Objectives: The mechanisms of spinal cord stimulation (SCS) are insufficiently understood. Conditioned pain modulation (CPM) measures how a painful stimulus is affected by a second painful stimulus. We investigated whether cortical evoked response can be used to evaluate CPM in a patient treated with burst, tonic and sham SCS. Methods: A 40-year-old patient underwent 3 magnetoencephalography sessions (burst, tonic, sham SCS) with 1-week intervals. Painful electrical stimuli were applied to the tibial nerve before, during and after CPM (conditioning: icepack on forearm). Evoked responses were analysed in the primary somatosensory and anterior cingulate cortices. Results: Before CPM, the highest evoked response amplitude occurred under sham SCS, followed by tonic SCS. During CPM pain ratings remained unchanged. However, CPM reduced evoked response amplitudes in the primary somatosensory cortex under tonic and sham SCS and in the anterior cingulate cortex under all SCS paradigms. Conclusions: CPM reduced evoked response amplitudes, while pain ratings were unaffected, suggesting neurophysiological measures provide additional insights into CPM effects. Tonic and burst SCS both appeared to reduce cortical capacity to attend to stimuli, with burst showing the greatest effect. Significance: Cortical responses offer a valuable tool to assess pain pathways. Larger scale studies are needed to enhance our understanding of SCS mechanisms.
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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) | 0.001 | 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) | 0.006 | 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".