The neural control of interlimb coordination during mammalian locomotion
Bibliographic record
Abstract
Neuronal networks within the spinal cord directly control rhythmic movements of the arms/forelimbs and legs/hindlimbs during locomotion in mammals. For an effective locomotion, these networks must be flexibly coordinated to allow for various gait patterns and independent use of the arms/forelimbs. This coordination can be accomplished by mechanisms intrinsic to the spinal cord, somatosensory feedback from the limbs, and various supraspinal pathways. Incomplete spinal cord injury disrupts some of the pathways and structures involved in interlimb coordination, often leading to a disruption in the coordination between the arms/forelimbs and legs/hindlimbs in animal models and in humans. However, experimental spinal lesions in animal models to uncover the mechanisms coordinating the limbs have limitations due to compensatory mechanisms and strategies, redundant systems of control, and plasticity within remaining circuits. The purpose of this review is to provide a general overview and critical discussion of experimental studies that have investigated the neural mechanisms involved in coordinating the arms/forelimbs and legs/hindlimbs during mammalian 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".