Effects of spatial attention and limb position on the cortical interaction of bilateral noxious inputs
Bibliographic record
Abstract
Bilateral noxious inputs interact in the brain to provide a better representation of physical threat. In the present study, we investigated the effects of spatial attention and limb position on this interaction. Painful laser stimuli were applied randomly on the right hand or on both hands, while varying spatial attention (focal or overall) and limb position (hands near or far from each other). Pain perception and laser-evoked potentials (N1, N2, P2) were compared between conditions in 27 healthy volunteers. Compared with unilateral stimulation, bilateral stimulation increased pain (p = .004), the N2 (p = .0015) and P2 (p < .001) amplitude. The effects on pain and the P2 were greater when hands were in the near compared with the far position (p < .05). The effect on pain was also greater for overall compared with focal pain rating (p = .003). In addition, the N1 amplitude was greater for bilateral stimulation when hands were in the far compared with the near position (p = .01). These results show that increased brain responses and pain for bilateral compared with unilateral noxious stimulation are modulated differentially by spatial attention and limb position. This suggests that the integration of noxious inputs occurs through partially independent pain-related processes, that it is modulated by limb position, and that it is partially independent of pain perception. We propose that this is necessary to produce coordinated, flexible and adapted defensive 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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".