Reduction of intractable deafferentation pain by navigation-guided repetitive transcranial magnetic stimulation of the primary motor cortex
Bibliographic record
Abstract
The precentral gyrus (M1) is a representative target for electrical stimulation therapy of pain. To date, few researchers have investigated whether pain relief is possible by stimulation of cortical areas other than M1. According to recent reports, repetitive transcranial magnetic stimulation (rTMS) can provide an effect similar to that of electrical stimulation. With this in mind, we therefore examined several cortical areas as stimulation targets using a navigation-guided rTMS and compared the effects of the different targets on pain. Twenty patients with intractable deafferentation pain received rTMS of M1, the postcentral gyrus (S1), premotor area (preM), and supplementary motor area (SMA). Each target was stimulated with ten trains of 10-s 5-Hz TMS pulses, with 50-s intervals in between trains. Intensities were adjusted to 90% of resting motor thresholds. Thus, a total of 500 stimuli were applied. Sham stimulations were undertaken at random. The effect of rTMS on pain was rated by patients using a visual analogue scale (VAS) and the short form of the McGill Pain Questionnaire (SF-MPQ). Ten of the 20 patients (50%) indicated that stimulation of M1, but not other areas, provided significant and beneficial pain relief (p<0.01). Results indicated a statistically significant effect lasting for 3 hours after the stimulation of M1 (p<0.05). Stimulation of other targets was not effective. The M1 was the sole target for treating intractable pain with rTMS, in spite of the fact that M1, S1, preM, and SMA are located adjacently.
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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) | 0.001 | 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".