Spinal and supraspinal processing of thermal stimuli: An fMRI study
Bibliographic record
Abstract
PURPOSE: To assess and characterize responses to innocuous/noxious thermal stimuli and heat allodynia using functional spinal magnetic resonance imaging (spinal fMRI). MATERIALS AND METHODS: Spinal/supraspinal activation patterns of 16 healthy subjects were investigated by applying painful and nonpainful heat stimuli to dermatome C6 baseline and after sensitization with the heat/capsaicin model using fMRI (3T, single-shot TSE, TR 9000 msec, TE 38 msec, FOV 288 × 144 × 20 mm, matrix 192 × 96, voxel size 1 × 1 × 2 mm). RESULTS: Increased activity was observed in ipsi- and contralateral ventral and dorsal spinal horn during noxious heat and heat allodynia. During noxious heat, but not during heat allodynia, activations were visible in the periaqueductal gray, ipsilateral cuneiform nucleus, and ipsilateral dorsolateral pontine tegmentum (DLPT). However, during heat allodynia activations were observed in bilateral ruber nuclei, contralateral DLPT, and rostral ventromedial medulla oblongata (RVM). Activations in contralateral subnucleus reticularis dorsalis (SRD) were visible during both noxious heat and heat allodynia (T >2.5, P < 0.01 for all of the above). After sensitization, activations in RVM and SRD correlated with activations in the ipsilateral dorsal horn of the spinal cord (R = 0.52-0.98, P < 0.05). CONCLUSION: Spinal fMRI successfully demonstrates increased spinal activity and secondary changes in activation of supraspinal centers involved in pain modulation caused by peripheral nociceptor sensitization. J. Magn. Reson. Imaging 2015;41:1046-1055. © 2014 Wiley Periodicals, Inc.
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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".