Spatiotemporal control of interlimb coordination during transverse split-belt locomotion with 1:1 or 2:1 coupling patterns in intact adult cats
Bibliographic record
Abstract
Interlimb coordination must be flexible to adjust to an ever-changing environment. Here adjustments in interlimb coordination were quantified during tied-belt (equal speed of the fore- and hindlimbs) and transverse split-belt (unequal speed of the fore- and hindlimbs) locomotion in five intact adult cats. Cats performed tied-belt locomotion at 0.4 m/s and 0.8 m/s. For transverse split-belt locomotion, the forelimbs stepped at 0.4 m/s and 0.8 m/s while the hindlimbs stepped at 0.8 m/s (4F8H condition) and 0.4 m/s (8F4H condition), respectively. In the 8F4H condition, the forelimbs could take two steps within one hindlimb cycle, or a 2:1 forelimb-hindlimb relationship. The sequence of limbs contacting the ground and the duration of support periods were differentially modified if the forelimbs stepped faster or slower than the hindlimbs. During transverse split-belt locomotion, the hindlimbs performed longer strides when the forelimbs took shorter strides. In the 8F4H condition with a 2:1 forelimb-hindlimb relationship, phase and gap intervals for the first and second steps were found around certain values and were not randomly distributed, indicating that a new coupling pattern was established. However, temporal and spatial coordination indexes revealed that bilateral coordination between hindlimbs was less accurate and more variable with a 2:1 coupling pattern. Importantly, the animals did not stumble, indicating that spatial and temporal adjustments in interlimb coordination allowed the animals to maintain dynamic stability. The results provide a better understanding of the spatiotemporal adjustments that take place among the four limbs during locomotion when interlimb coordination is challenged.
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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) | 0.000 | 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".