Differentiation of Visceral and Cutaneous Pain in the Human Brain
Why this work is in the frame
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Bibliographic record
Abstract
The widespread convergence of information from visceral, cutaneous, and muscle tissues onto CNS neurons invites the question of how to identify pain as being from the viscera. Despite referral of visceral pain to cutaneous areas, individuals regularly distinguish cutaneous and visceral pain and commonly have contrasting behavioral reactions to each. Our study addresses this dilemma by directly comparing human neural processing of intensity-equated visceral and cutaneous pain. Seven subjects underwent fMRI scanning during visceral and cutaneous pain produced by balloon distention of the distal esophagus and contact heat on the midline chest. Stimulus intensities producing nonpainful and painful sensations, interleaved with rest periods, were presented in each functional run. Analyses compared painful to nonpainful conditions. A similar neural network, including secondary somatosensory and parietal cortices, thalamus, basal ganglia, and cerebellum, was activated by visceral and cutaneous painful stimuli. However, cutaneous pain evoked higher activation bilaterally in the anterior insular cortex. Further, cutaneous but not esophageal pain activated ventrolateral prefrontal cortex, despite higher affective scores for visceral pain. Visceral but not cutaneous pain activated bilateral inferior primary somatosensory cortex, bilateral primary motor cortex, and a more anterior locus within anterior cingulate cortex. Our results reveal a common cortical network subserving cutaneous and visceral pain that could underlie similarities in the pain experience. However, we also observed differential activation patterns within insular, primary somatosensory, motor, and prefrontal cortices that may account for the ability to distinguish visceral and cutaneous pain as well as the differential emotional, autonomic and motor responses associated with these different sensations.
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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 | 0.000 | 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) | 0.000 | 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 it