The effects of local forearm heating and cooling on motor unit properties during submaximal contractions
Bibliographic record
Abstract
NEW FINDINGS: What is the central question of this study? How do temperature manipulations affect motor unit (MU) properties during submaximal contractions to the same relative percentage of maximal force? What is the main finding and its importance? MU recruitment patterns are affected by temperature manipulations at the forearm. However, the relationship between MU potential amplitude and recruitment threshold indicates no change to the order or recruitment. Additionally, the MU potential amplitude and firing rate relationship was affected by temperature, suggesting that smaller MUs are more affected by temperature changes than larger MUs. ABSTRACT: Temperature impacts muscle contractile properties, such that experiments with workloads based on thermoneutral values will produce different relative intensities if maximal force changes due to muscle temperature. We investigated how temperature affected motor unit (MU) properties with contractions performed at the same normalized percentage of maximal force. Twenty participants (10 females) completed evoked, maximal, and trapezoidal voluntary contractions during thermoneutral-, hot-, and cold-temperature conditions. Forearm temperature was established using 25 min of neutral (∼32°C), hot (∼44°C) or cold (∼13°C) water circulated through a tube-lined sleeve. Flexor carpi radialis MU properties were assessed with contractions at 30% and 60% MVC relative to each temperature using surface electromyography decomposition. Changes to contractile properties and electromechanical delay from the evoked twitch suggest that muscle contractility was changed from the thermal manipulations (effect size (d) ≥ 0.42, P < 0.05). Maximal force was not different between neutral and hot conditions (d = 0.16, P > 0.05) but decreased in the cold (d ≥ 0.34, P < 0.05). For both contraction intensities, MU potential (MUP) amplitude was larger and duration was longer in the cold compared to neutral and hot conditions (d ≥ 1.24, P < 0.05). Cumulative probability density for the number of MUs recruited revealed differences in MU recruitment patterns among temperature conditions. The relationship between MU recruitment threshold and firing rate or MUP amplitude was not different among temperature conditions (P > 0.05); however, the relationship between MUP amplitude and firing rate was (P < 0.05). Local temperature manipulations appear to affect MU recruitment patterns, which may act as compensatory mechanisms to the changes in muscle viscosity and contractile properties due to local temperature changes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".