Motor and Sensory Axon Excitability Properties From the Median and Ulnar Nerves and the Effects of Age on These Properties
Bibliographic record
Abstract
PURPOSE: Threshold tracking is a new noninvasive approach for detecting axonal excitability changes in vivo. In this study, the authors compared the excitability indices of motor and sensory axons of median and ulnar nerves to determine whether the two nerves behave in a similar or a noninterchangeable way. They also examined whether age affects these indices. METHODS: Seventy normal subjects aged 22-70 years (mean, 36.7 ± 12.5 years) were recruited. Multiple excitability indices were measured in both motor and sensory axons from median and ulnar nerves. RESULTS: The threshold and rheobase were significantly higher for the ulnar motor axons recorded at the first dorsal interosseous muscle than for the median motor axons at the abductor pollicis brevis muscle. In contrast, the strength-duration time constant was decreased, threshold electrotonus reduction (in both depolarizing and hyperpolarizing directions) was significantly smaller, I/V slope was decreased, and subexcitability was reduced for the ulnar motor axons. Excitability indices measured in the sensory axons of both nerves were not overtly different. In R-square analysis, age had a homogeneous influence on sensory axon excitability but heterogeneous influence on motor axon excitability. CONCLUSIONS: The excitability indices may be interchangeable for sensory axons but not motor axons. The authors therefore recommend recording motor axonal excitability in various muscle groups rather than a single muscle group.
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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".