Chronic inactivation of the contralesional hindlimb motor cortex after thoracic spinal cord hemisection impedes locomotor recovery in the rat
Bibliographic record
Abstract
After incomplete spinal cord injury (SCI), cortical plasticity is involved in hindlimb locomotor recovery. Nevertheless, whether cortical activity is required for motor map plasticity and recovery remains unresolved. Here, we combined a unilateral thoracic spinal cord injury (SCI) with a cortical inactivation protocol that uncovered a functional role of contralesional cortical activity in hindlimb recovery and ipsilesional map plasticity. In adult rats, left hindlimb paralysis was induced by sectioning half of the spinal cord at the thoracic level (hemisection) and we used a continuous infusion of muscimol (GABAA agonist, 10 mM, 0.11 µl/h) delivered via implanted osmotic pump (n = 9) to chronically inactivate the contralesional hindlimb motor cortex. Hemisected rats with saline infusion served as a SCI control group (n = 8), and intact rats with muscimol infusion served as an inactivation control group (n = 6). Locomotion was assessed in an open field, on a horizontal ladder, and on a treadmill prior to and for three weeks after hemisection. Cortical inactivation after hemisection significantly impeded hindlimb locomotor recovery in all tasks and specifically disrupted the ability of rats to generate proper flexion of the affected hindlimb during stepping compared to SCI controls, with no significant effect of inactivation in intact rats. Chronic and acute (n = 4) cortical inactivation after hemisection also significantly reduced the representation of the affected hindlimb in the ipsilesional motor cortex derived with intracortical microsimulation (ICMS). Our results provide evidence that residual activity in the contralesional hindlimb motor cortex after thoracic hemisection contributes to spontaneous locomotor recovery and map plasticity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".