Neural activity in trigeminal neuralgia patients with sensory and motor stimulations: A pilot functional MRI study
Bibliographic record
Abstract
OBJECTIVE: Trigeminal neuralgia (TN) is a neuropathic pain syndrome that typically exhibits paroxysmal pain. However, the true mechanism of pain processing is unclear. We aim to evaluate the neural activity changes, before and after radiofrequency rhizotomy, in TN patients using functional MRI (fMRI) with sensory and motor stimulations. METHODS: Six patients with classical TN participated in the study. Each patient underwent two boxcar paradigms of fMRI tasks: air-sensation and jaw-clenching around 1-3 weeks before and after the surgical intervention. McGill Pain Questionnaire (MPQ) was used to evaluate the pain intensity prior to fMRI study. RESULTS: Before rhizotomy, the jaw-clenching stimulation yielded reduced brain activation in primary motor (M1) and primary (SI) and secondary somatosensory (SII) cortices. Following intervention, activation in those regions returned to near normal levels observed in healthy subjects. For air-sensation stimulation, several pain and pain modulation regions such as right thalamus, right putamen, insula, and brainstem, were activated before the intervention, but subsided after the intervention. This correlated well with the change of MPQ scores (p < 0.01). CONCLUSIONS: In our study, we observed significant pain reduction accompanied by increased motor activities after rhizotomy in patients with TN. We hypothesize that the reduced motor activities identified in fMRI may be reversed after the treatment with radiofrequency rhizotomy. More research is warranted.
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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".