Split-Belt Treadmill Stepping in Infants Suggests Autonomous Pattern Generators for the Left and Right Leg in Humans
Bibliographic record
Abstract
The behavior of the pattern generator for walking in human infants (7-12 months of age) was studied by supporting the infants to step on a split-belt treadmill. The treadmill belts could be run at the same speed (tied-belt), different speeds, or in different directions (split-belt). We determined whether the legs could operate independently under these conditions, as demonstrated by taking different numbers of steps or by stepping in different directions. Video, surface electromyography, electrogoniometry, and force platform data were recorded. The majority of infants who could step under tied-belt conditions also stepped under split-belt conditions. During forward stepping at low speed differentials between the two belts (ratio, <4), infants adopted a step cycle duration that was intermediate between that expected from tied-belt stepping at each of the speeds. At large speed differentials between the two belts (ratio, 7-22), the infants took extra steps on the fast leg during the stance phase on the slow leg. When the two belts ran in opposite directions, one leg stepped forward, and the other stepped backward. During all forms of stepping, the legs maintained a reciprocal relationship, so that swing phase occurred in one leg at a time. Timing of muscle activity suggests a strong inhibition between the flexor-generating centers on each side and a weaker inhibition between the extensor-generating centers. The stepping behavior resembled that reported for other animals under similar conditions, suggesting that the pattern generator for each limb is autonomous but interacts with its counterpart for the contralateral limb.
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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 | 0.001 |
| 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".