Pain is what you think: functional magnetic resonance imaging evidence toward a cognitive and affective approach for pain research
Bibliographic record
Abstract
The sensory/discriminative domain of pain is often given more consideration than the cognitive and affective influences that ultimately make pain what it is: a highly subjective experience that is based on an individual's life history and experiences. While many investigations of the underlying mechanisms of pain have focused on solely noxious stimuli, few have compared somatosensory stimuli that cross the boundary from innocuous to noxious. Of those that have, there is little consensus on the similarities and differences in neural signaling across these sensory domains. The purpose of this study was to apply our established network connectivity analyses toward the goal of understanding the neural mechanisms behind sensory, cognitive, and affective responses to noxious and innocuous stimuli. Functional MRI data were collected from 19 healthy women and men that experienced warm and hot thermal stimuli across multiple trials. This is a within-subjects cross-sectional experimental study with repeated measures. Ratings of stimulus intensity and unpleasantness that were collected during each run confirmed significant perceptual differences between the two types of stimuli. Despite this finding, no group differences in network connectivity were found across conditions. When individual differences related to pain ratings were investigated, subtle differences were found in connectivity that could be attributed to sensory and association regions in the innocuous condition, and cognitive, affective, and autonomic regions in the pain condition. These results were reflected in the time-course data for each condition. Overall, signaling mechanisms for innocuous and noxious somatosensation are intricately linked, but pain-specific perception appears to be driven by our psychological and autonomic states.
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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 | 0.074 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".