Spinal fMRI Reveals Decreased Descending Inhibition during Secondary Mechanical Hyperalgesia
Bibliographic record
Abstract
Mechanical hyperalgesia is one distressing symptom of neuropathic pain which is explained by central sensitization of the nociceptive system. This sensitization can be induced experimentally with the heat/capsaicin sensitization model. The aim was to investigate and compare spinal and supraspinal activation patterns of identical mechanical stimulation before and after sensitization using functional spinal magnetic resonance imaging (spinal fMRI). Sixteen healthy subjects (6 female, 10 male, mean age 27.2 ± 4.0 years) were investigated with mechanical stimulation of the C6 dermatome of the right forearm during spinal fMRI. Testing was always performed in the area outside of capsaicin application (i.e. area of secondary mechanical hyperalgesia). During slightly noxious mechanical stimulation before sensitization, activity was observed in ipsilateral dorsolateral pontine tegmentum (DLPT) which correlated with activity in ipsilateral spinal cord dorsal gray matter (dGM) suggesting activation of descending nociceptive inhibition. During secondary mechanical hyperalgesia, decreased activity was observed in bilateral DLPT, ipsilateral/midline rostral ventromedial medulla (RVM), and contralateral subnucleus reticularis dorsalis, which correlated with activity in ipsilateral dGM. Comparison of voxel-based activation patterns during mechanical stimulation before/after sensitization showed deactivations in RVM and activations in superficial ipsilateral dGM. This study revealed increased spinal activity and decreased activity in supraspinal centers involved in pain modulation (SRD, RVM, DLPT) during secondary mechanical hyperalgesia suggesting facilitation of nociception via decreased endogenous inhibition. Results should help prioritize approaches for further in vivo studies on pain processing and modulation in humans.
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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".