Parallel cortical-brainstem pathways to attentional analgesia
Bibliographic record
Abstract
Pain demands attention, yet pain can be reduced by focusing attention elsewhere. The neural processes involved in this robust psychophysical phenomenon, attentional analgesia, are still being defined. Our previous fMRI study linked activity in the brainstem triad of locus coeruleus (LC), rostral ventromedial medulla (RVM) and periaqueductal grey (PAG) with attentional analgesia. Here we identify and model the functional interactions between these regions and the cortex in healthy human subjects (n = 57), who received painful thermal stimuli whilst simultaneously performing a visual attention task. RVM activity encoded pain intensity while contralateral LC activity correlated with attentional analgesia. Psycho-Physiological Interaction analysis and Dynamic Causal Modelling identified two parallel paths between forebrain and brainstem. These connections are modulated by attentional demand: a bidirectional anterior cingulate cortex (ACC) - right-LC loop, and a top-down influence of task on ACC-PAG-RVM. By recruiting discrete brainstem circuits, the ACC is able to modulate nociceptive input to reduce pain in situations of conflicting attentional demand.
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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".