Dissection of perceptual, motor and autonomic components of brain activity evoked by noxious stimulation
Bibliographic record
Abstract
In the past two decades, functional brain imaging has considerably advanced our knowledge of cerebral pain processing. However, many important links are still missing in our understanding of brain activity in relation to the regulation of pain-related physiological responses. This fMRI study investigates the cerebral correlates of pain (rating), motor responses (RIII-reflex) and autonomic activity (skin conductance response; SCR) evoked by noxious electrical stimulation. Stimulus intensity was adjusted individually based on the RIII threshold to control for differences in peripheral processes and baseline spinal activation. Covariance analyses were used to reveal individual differences in brain activity uniquely associated with individual differences in pain, RIII and SCR. Shock-evoked activity in cingulate, medial orbitofrontal and parahippocampal regions predicted pain sensitivity. Moreover, lateral orbitofrontal and cingulate areas showed strong positive associations with individual differences in motor reactivity but negative associations with autonomic reactivity. Notably, individual differences in OFC activation was almost fully accounted by the combination of individual measures of autonomic and motor reactivity (R(2)=0.93). Additionally, trial-to-trial fluctuations of RIII-reflex and SCR (within-subjects) were proportional to shock-evoked responses in subgenual cingulate cortex (RIII), anterior insula (SCR) and midcingulate cortex (SCR and RIII). Together, these results confirm that individual differences in perceptual, motor, and autonomic components of pain reflect robust individual differences in brain activity. Furthermore, the brain correlates of trial-to-trial fluctuations in pain responses provide additional evidence for a partial segregation of sub-systems involved more specifically in the ongoing monitoring, and possibly the regulation, of pain-related motor and autonomic responses.
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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) | 0.001 | 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".