Individual differences in conditioned pain modulation are associated with functional connectivity within the descending antinociceptive pathway
Bibliographic record
Abstract
ABSTRACT: The perception of pain and ability to cope with it varies widely amongst people, which in part could be due to the presence of inhibitory (antinociceptive) or facilitatory (pronociceptive) effects in conditioned pain modulation (CPM). This study examined whether individual differences in CPM reflect functional connectivity (FC) strengths within nodes of the descending antinociceptive pathway (DAP). A heat-based CPM paradigm and resting-state functional magnetic resonance imaging (rs-fMRI) were used to test the hypothesis that an individual's capacity to exhibit inhibitory CPM (changes in test stimuli [TS] pain due to a conditioning stimulus [CS]) reflects FC of the subgenual anterior cingulate cortex (sgACC), periaqueductal gray (PAG), and rostral ventromedial medulla (RVM). A total of 151 healthy participants (72 men, 79 women) underwent CPM testing and rs-fMRI. Three types of CPM were identified based on the effect of the CS on TS pain: (1) Antinociception: CS reduced TS pain in 45% of participants, (2) No-CPM: CS did not change TS pain in 15% of participants, and (3) Pronociception: CS increased TS pain in 40% of participants. Only the Antinociceptive subgroup exhibited FC between the left sgACC and PAG, right sgACC and PAG, and RVM and PAG. Furthermore, only the Antinociceptive subgroup exhibited a correlation of both left and right sgACC-RVM FC (medium effect sizes) with CPM effect magnitude. Women, compared with men were more likely to be categorized as pronociceptive. These data support the proposition that FC of the DAP reflects or contributes to inhibitory CPM.
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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 | 0.001 |
| 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) | 0.002 | 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".