Adaptive Plasticity in the Spinal Control of Left‐right Coordination During Locomotion
Bibliographic record
Abstract
Hindlimb (HL) locomotion recovers in chronic spinal‐transected cats following ankle extensors neurectomy (Bouyer et al. 2001), indicating compensatory spinal mechanisms. However, such recovery has only been tested during single‐belt treadmill locomotion at moderate speeds (0.35 m/s to 0.5 m/s). Here, HL locomotion was assessed at several speeds and left‐right speed differences during tied‐belt (equal left‐right speeds) and split‐belt (unequal left‐right speeds) locomotion, respectively, in 4 chronic spinal‐transected cats implanted with chronic electrodes for EMG. Spinal transection was made at the last thoracic segments and cats were trained to recover HL locomotion. A unilateral denervation of the lateral gastrocnemius and soleus was made after stable HL locomotion had recovered, at least 1 month post‐transection. Denervation produced variable results between cats. In the most affected cat, the denervated HL made abnormal contacts with the paw dorsum and left and right HLs were not coordinated 1‐2 days post‐denervation, producing an unstable locomotion. Although the pattern gradually stabilized over several weeks, plantigrade placement of the denervated HL was facilitated only if the non‐denervated HL stepped faster during split‐belt locomotion. In the opposite split‐belt condition, the pattern remained unstable. In the least affected cat, although no abnormal paw placements were observed 1 day post‐denervation, HL locomotion was considerably more stable with the denervated HL stepping faster during split‐belt locomotion. Preliminary results suggest that ankle extensors are important for the spinal control of left‐right coordination and that adaptation can be shaped by split‐belt locomotion.
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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".