Protracted Exercise Without Overt Neuromuscular Fatigue Influences Cortical Excitability
Bibliographic record
Abstract
The authors' aim was to determine the cortical mechanisms that underlie the transition from effective performance to its disruption. They thus used transcranial magnetic stimulation (TMS) to study changes of corticospinal excitability after a motor exercise that did not produce overt or perceived neuromuscular fatigue. Forty-four subjects performed either 5 or 10 min of repetitive finger movements paced by tones at 2 Hz, a frequency below the spontaneous movement rate. Changes of corticospinal excitability were assessed with TMS at rest and during motor response preparation (premovement facilitation paradigm). Over time, variability of movement rate increased, while the average movement rate shifted toward self-paced rhythms, without significant changes in other kinematic parameters. Amplitudes of motor evoked potentials at rest decreased depending on task duration and TMS intensity. Moreover, 5-min exercise induced fully compensatory increases in premovement facilitation, while 10-min exercise produced partially compensatory increases with loss of temporal modulation. Our findings suggest that protracted exercise induces significant decrements in corticospinal excitability with initial impairment of the phasic motor neurons that are recruited at higher stimulus intensities. Changes in premovement facilitation likely represent compensation of premotor areas for decreased efficiency of the primary motor cortex induced by exercise.
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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".