Functional magnetic resonance imaging in rats subjected to intense electrical and noxious chemical stimulation of the forepaw
Bibliographic record
Abstract
We examined whether cerebral activation to two different intense and painful stimuli could be detected using functional magnetic resonance imaging (fMRI) in alpha-chloralose anesthetized rats. Experiments were performed using a 9.4 T magnet and a surface coil centered over the forebrain. A set of gradient echo images were acquired and analyzed using our software based on fuzzy cluster analysis (EvIdent). Following the injection of 50 microl of formalin (5%) into the forepaw we observed a regional increase in signal intensity in the MR images in all animals. Anterior cingulate cortex, frontal cortex and sensory-motor cortex were some of the regions that activated frequently and often bilaterally. Surprisingly, activation appeared sequentially, often occurring first in either the right or the left hemisphere with a separation of seconds to minutes between peak activations. Morphine pre-treatment (1 mg/kg, i. v.) delayed and/or reduced the intensity of the activation resulting in a decrease in the overall response. Following episodes of intense electrical stimulation, produced by two brief stimulations (15 V, 0. 3 ms, 3 Hz) of the forepaw, activation was observed consistently in the sensory-motor cortex contralateral to the stimulation. Activation also occurred frequently in the anterior cingulate cortex, ipsilateral sensory-motor cortex and frontal cortical regions. All these regions of activation were markedly reduced during nitrous oxide inhalation. Treatment with morphine resulted in an inhibition of the activation response to electrical stimulation in most regions except for sensory-motor cortex. Thus, electrical and chemical noxious stimuli activated regions that are known to be involved in the central processing of pain and morphine modified the activation observed. fMRI combined with appropriate exploratory data analysis tools could provide an effective new tool with which to study novel analgesics and their effects on the CNS processing of pain in animal models.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".