Afferent Regulation of Leg Motor Cortex Excitability After Incomplete Spinal Cord Injury
Bibliographic record
Abstract
An incomplete spinal cord injury (SCI) impairs neural conduction along spared ascending sensory pathways to disrupt the control of residual motor movements. To characterize how SCI affects the activation of the motor cortex by spared ascending sensory pathways, we examined how stimulation of leg afferents facilitates the excitability of the motor cortex in subjects with incomplete SCI. Homo- and heteronymous afferents to the tibialis anterior (TA) representation in the motor cortex were electrically stimulated, and the responses were compared with uninjured controls. In addition, we examined if cortical excitability could be transiently increased by repetitively pairing stimulation of spared ascending sensory pathways with transcranial magnetic stimulation (TMS), an intervention termed paired associative stimulation (PAS). In uninjured subjects, activating the tibial nerve at the ankle 45-50 ms before a TMS pulse in a conditioning-test paradigm facilitated the motor-evoked potential (MEP) in the heteronymous TA muscle by twofold on average. In contrast, prior tibial nerve stimulation did not facilitate the TA MEP in individuals with incomplete SCI (n = 8 SCI subjects), even in subjects with less severe injuries. However, we provide evidence that ascending sensory inputs from the homonymous common peroneal nerve (CPN) can, unlike the heteronymous pathways, facilitate the motor cortex to modulate the TA MEP (n = 16 SCI subjects) but only in subjects with less severe injuries. Finally, by repetitively coupling CPN stimulation with coincident TA motor cortex activation during PAS, we show that 7 of 13 SCI subjects produced appreciable (>20%) facilitation of the MEP following the intervention. The increase in corticospinal tract excitability by PAS was transient (<20 min) and tended to be more prevalent in SCI subjects with stronger functional ascending sensory pathways.
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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".