Postural dependence of human locomotion during gait initiation
Bibliographic record
Abstract
The initiation of human walking involves postural motor actions for body orientation and balance stabilization that must be effectively integrated with locomotion to allow safe and efficient transport. Our ability to coordinately adapt these functions to environmental or bodily changes through error-based motor learning is essential to effective performance. Predictive compensations for postural perturbations through anticipatory postural adjustments (APAs) that stabilize mediolateral (ML) standing balance normally precede and accompany stepping. The temporal sequencing between these events may involve neural processes that suppress stepping until the expected stability conditions are achieved. If so, then an unexpected perturbation that disrupts the ML APAs should delay locomotion. This study investigated how the central nervous system (CNS) adapts posture and locomotion to perturbations of ML standing balance. Healthy human adults initiated locomotion while a resistance force was applied at the pelvis to perturb posture. In experiment 1, using random perturbations, step onset timing was delayed relative to the APA onset indicating that locomotion was withheld until expected stability conditions occurred. Furthermore, stepping parameters were adapted with the APAs indicating that motor prediction of the consequences of the postural changes likely modified the step motor command. In experiment 2, repetitive postural perturbations induced sustained locomotor aftereffects in some parameters (i.e., step height), immediate but rapidly readapted aftereffects in others, or had no aftereffects. These results indicated both rapid but transient reactive adaptations in the posture and gait assembly and more durable practice-dependent changes suggesting feedforward adaptation of locomotion in response to the prevailing postural conditions.
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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".