The nociceptive withdrawal reflex of the trunk is organized with unique muscle receptive fields and motor strategies
Bibliographic record
Abstract
Noxious stimuli induce a nociceptive withdrawal reflex (NWR) to protect the tissue from injury. Although the NWR was once considered as a stereotyped response, previous studies report distinct responses depending on the stimulation site and context for limbs. We aimed to determine whether noxious stimuli over the trunk produced adaptable complex NWR. We hypothesized that organization of the NWR of the trunk muscle would vary with the site of noxious input and would differ between body and spine postures, which modify the potential for specific muscles to remove threat. Fourteen participants were tested in sitting and three lumbar spine postures in side lying (neutral, flexion and extension). Noxious electrical stimuli were applied over the sacrum, spinous process of L3 and T12, lateral side of the 8th rib and anterior midline. NWR latency and amplitude were recorded with surface electromyography (EMG) electrodes over different trunk muscles. Distinct patterns of muscle activation depended on the stimulation site and were consistent with motor strategies needed to withdraw from the noxious stimuli. The NWR pattern differed between body positions, with less modulation observed in sitting than side lying. Spine posture did not affect the NWR organisation. Our results suggest the circuits controlling trunk muscle NWR presents with adaptability as a function of stimulation site and body position by utilizing the great complexity of the trunk muscle system to produce an efficient protective response. This suggests that the central nervous system (CNS) uses multiple adaptable strategies that are unique depending on which context the noxious stimuli are applied.
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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) | 0.001 | 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".