Capsaicin as a source for painful stimulation in functional MRI
Bibliographic record
Abstract
Functional magnetic resonance imaging (fMRI) was used to examine the brain processing of capsaicin-induced painful stimulation in the alpha-chloralose anesthetized rat. Experiments were performed on a 9.4-T magnet (Magnex, UK) with Avance console (Bruker, Germany) using a surface coil tuned to 400.5 MHz centred over the rat forebrain. Gradient-echo images of two slices, with an echo time of 25 msec, repetition time of 70 msec, and 50 repetitions, were acquired per experiment. These images were analyzed using a fuzzy cluster analysis technique (EvIdent). Activation of areas of the brain known to be associated with the processing of pain, namely the anterior cingulate (bilateral), frontal cortex (bilateral), and sensory motor cortex (contralateral), was found in all animals (N = 6) following injection of 25 microl of capsaicin (128 microg/mL in 7.5% dimethylsulfoxide [DMSO]) into the dorsal forepaw. It is possible to reproduce the pain response in a given animal several times throughout the course of an experiment, provided that sufficient time is allowed between capsaicin injections. This acute phase of capsaicin-induced pain involving stimulation of C polymodal nociceptors was examined by functional imaging. There was a substantial initial increase in activation in regions of the brain associated with pain and there was a trend towards increasing activation with repeated stimulations. Treatment with morphine (3 mg/kg, intravenously) was found to substantially reduce, if not completely eliminate, the areas of functional activation associated with physiologic pain (anterior cingulate and frontal cortex) after C-nociceptor stimulation with capsaicin (N = 6). FMRI involving capsaicin-induced painful stimulation could prove to be an effective tool for the study of novel analgesics and the central nervous system processing of pain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".