Spinal and corticospinal excitability in response to reductions in skin and core temperatures via whole-body cooling
Bibliographic record
Abstract
Cold stress impairs fine and gross motor movements. Although peripheral effects of muscle cooling on performance are well understood, less is known about central mechanisms. This study characterized corticospinal and spinal excitability during surface cooling, reducing skin (Tsk) and esophageal (Tes) temperatures. Ten subjects (3 females) wore a liquid-perfused suit and were cooled (9 °C perfusate, 90 min) and rewarmed (41 °C perfusate, 30 min). Transcranial magnetic stimulation (eliciting motor evoked potentials [MEPs]), as well as transmastoid (eliciting cervicomedullary evoked potentials [CMEPs]) and brachial plexus (eliciting maximal compound motor action potentials [Mmax]) electrical stimulation, were applied at baseline, every 20 min during cooling, and following rewarming. Sixty minutes of cooling reduced Tsk by 9.6 °C (P < 0.001), but Tes remained unchanged (P = 0.92). Tes then decreased by ∼0.6 °C in the next 30 min of cooling (P < 0.001). Eight subjects shivered. During rewarming, shivering was abolished, and Tsk returned to baseline, while Tes did not increase. During cooling and rewarming, Mmax, MEP, and MEP/Mmax remained unchanged from baseline. However, CMEP and CMEP/Mmax increased during cooling by ∼85% and 79% (P < 0.001), respectively, and remained elevated post-rewarming. The results suggest that spinal excitability is facilitated by reduced Tsk during cooling and reduced Tes during warming, while corticospinal excitability remains unchanged. ClinicalTrials.gov ID: NCT04253730. Novelty: This is the first study to characterize corticospinal and spinal excitability during whole-body cooling and rewarming in humans. Whole body cooling did not affect corticospinal excitability. Spinal excitability was facilitated during reductions in both skin and core temperatures.
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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".