Younger Is Not Always Better: Development of Locomotor Adaptation from Childhood to Adulthood
Bibliographic record
Abstract
New walking patterns can be learned over short timescales (i.e., adapted in minutes) using a split-belt treadmill that controls the speed of each leg independently. This leads to storage of a modified spatial and temporal motor pattern that is expressed as an aftereffect in regular walking conditions. Because split-belt walking is a novel task for adults and children alike, we used it to investigate how motor adaptation matures during human development. We also asked whether the immature pattern resembles that of people with cerebellar dysfunction, because we know that this adaptation depends on cerebellar integrity. Healthy children (3-18 years old) and adults, and individuals with cerebellar damage were adapted while walking on split belts (1:2 speed ratio). Adaptation and de-adaptation rates were quantified separately for temporal and spatial parameters. All healthy children and adults tested could learn the new timing at the same rate and showed significant aftereffects. However, children younger than 6 years old were unable to learn the new spatial coordination. Furthermore, children as old as age 11 years old showed slower rates of adaptation and de-adaptation of spatial parameters of walking. Young children showed patterns similar to cerebellar patients, with greater deficits in spatial versus temporal adaptation. Thus, although walking is a well-practiced, refined motor skill by late childhood (i.e., 11 years of age), the processes underlying learning new spatial relationships between the legs are still developing. The maturation of locomotor adaptation follows at least two time courses, which we propose is determined by the developmental state of the cerebellum.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".