State- and Condition-Dependent Modulation of the Hindlimb Locomotor Pattern in Intact and Spinal Cats Across Speeds
Bibliographic record
Abstract
Locomotion after complete spinal cord injury (spinal transection) in animal models is usually evaluated in a hindlimb-only condition with the forelimbs suspended or placed on a stationary platform and compared with quadrupedal locomotion in the intact state. However, because of the quadrupedal nature of movement in these animals, the forelimbs play an important role in modulating the hindlimb pattern. This raises the question: whether changes in the hindlimb pattern after spinal transection are due to the state of the system (intact versus spinal) or because the locomotion is hindlimb-only. We collected kinematic and electromyographic data during locomotion at seven treadmill speeds before and after spinal transection in nine adult cats during quadrupedal and hindlimb-only locomotion in the intact state and hindlimb-only locomotion in the spinal state. We attribute some changes in the hindlimb pattern to the spinal state, such as convergence in stance and swing durations at high speed, improper coordination of ankle and hip joints, a switch in the timing of knee flexor and hip flexor bursts, modulation of burst durations with speed, and incidence of bi-phasic bursts in some muscles. Alternatively, some changes relate to the hindlimb-only nature of the locomotion, such as paw placement relative to the hip at contact, magnitude of knee and ankle yield, burst durations of some muscles and their timing. Overall, we show greater similarity in spatiotemporal and EMG variables between the two hindlimb-only conditions, suggesting that the more appropriate pre-spinal control is hindlimb-only rather than quadrupedal 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".