Incomplete spinal cord injury promotes durable functional changes within the spinal locomotor circuitry
Bibliographic record
Abstract
While walking in a straight path, changes in speed result mainly from adjustments in the duration of the stance phase while the swing phase remains relatively invariant, a basic feature of the spinal central pattern generator (CPG). To produce a broad range of locomotor behaviors, the CPG has to integrate modulatory inputs from the brain and the periphery and alter these swing/stance characteristics. In the present work we raise the issue as to whether the CPG can adapt or reorganize in response to a chronic change of supraspinal inputs, as is the case after spinal cord injury (SCI). Kinematic data obtained from six adult cats walking at different treadmill speeds were collected to calculate the cycle and subphase duration at different stages after a first spinal hemisection at T(10) and after a subsequent complete SCI at T(13) respectively aimed at disconnecting unilaterally and then totally the spinal cord from its supraspinal inputs. The results show, first, that the neural control of locomotion is flexible and responsive to a partial or total loss of supraspinal inputs. Second, we demonstrate that a hemisection induces durable plastic changes within the spinal locomotor circuitry below the lesion. In addition, this study gives new insights into the organization of the spinal CPG for locomotion such that phases of the step cycle (swing, stance) can be independently regulated for adapting to speed and also that the CPGs controlling the left and right hindlimbs can, up to a point, be regulated independently.
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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) | 0.001 | 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) | 0.002 | 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".