Training-Specific Neural Plasticity in Spinal Reflexes after Incomplete Spinal Cord Injury
Bibliographic record
Abstract
The neural plasticity of spinal reflexes after two contrasting forms of walking training was determined in individuals with chronic, motor-incomplete spinal cord injury (SCI). Endurance Training involved treadmill walking for as long as possible, and Precision Training involved walking precisely over obstacles and onto targets overground. Twenty participants started either Endurance or Precision Training for 2 months and then crossed over after a 2-month rest period to the other form of training for 2 months. Measures were taken before and after each phase of training and rest. The cutaneomuscular reflex (CMR) during walking was evoked in the soleus (SOL) and tibialis anterior muscles by stimulating the posterior tibial nerve at the ankle. Clonus was estimated from the EMG power in the SOL during unperturbed walking. The inhibitory component of the SOL CMR was enhanced after Endurance but not Precision Training. Clonus did not change after either form of training. Participants with lower reflex excitability tended to be better walkers (i.e., faster walking speeds) prior to training, and the reduction in clonus was significantly correlated with the improvement in walking speed and distance. Thus, reflex excitability responded in a training-specific way, with the reduction in reflex excitability related to improvements in walking function. Trial registration number is NCT01765153.
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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) | 0.001 | 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".