Central Fatigue Assessed by Transcranial Magnetic Stimulation in Ultratrail Running
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: The well-established central deficit in ultraendurance running races is not understood. The use of transcranial magnetic stimulation (TMS) in parallel with peripheral nerve stimulation provides insight into the source of these central changes. The aims of this study were to determine the presence and magnitude of voluntary activation deficits, especially supraspinal deficits, after a mountain trail-running race and to determine whether this can be explained by simultaneous changes in corticospinal excitability and intracortical inhibition. METHODS: Neuromuscular function (TMS and femoral nerve electrical stimulation) of the knee extensors was evaluated before and after a 110-km ultratrail in 25 experienced ultraendurance trail runners during maximal and submaximal voluntary contractions and in relaxed muscle. RESULTS: Voluntary activation assessed by both femoral nerve electrical stimulation (-26%) and TMS (-16%) decreased and were correlated (P < 0.01). Decreases in potentiated twitch and doublet amplitudes were correlated with decreased voluntary activation assessed by TMS (P < 0.05). There was increased motor-evoked potential (MEP) amplitude (P < 0.05) without change in cortical silent period (CSP) elicited by TMS at optimal stimulus intensity. Conversely, CSP at suboptimal TMS intensity increased (P < 0.05) without concurrent change in MEP amplitude. CONCLUSIONS: The present results demonstrate the development of a large central activation deficit assessed by TMS, indicating that cortical motoneurons are severely impaired in their ability to fire at optimal frequency or be fully recruited after an ultraendurance running race. MEP and CSP responses suggest a shift in the sigmoidal MEP-stimulus intensity relationship toward larger MEP at higher TMS intensity without change in inflection point of the curve and a left shift in the CSP-stimulus intensity relationship.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it