Neuromuscular organization during balance-correcting responses induced with platform-translation and upper body cable-pull perturbation methods
Bibliographic record
Abstract
Balance-correcting responses are fast, accurate, and functionally- and directionally-specific. However, there remains a lack of clarity in the literature as to how balance-correcting responses are organized, perhaps due to use of various perturbation methods. This study investigated the differences in neuromuscular organization of balance-correcting responses induced with platform-translation (PLAT) and upper body cable-pull (PULL) methods. Healthy males ( n = 15; age: 24.3 ± 3.0 years) underwent unexpected forward and backward PLAT and PULL perturbations of equivalent intensity. EMG of leg, thigh, and trunk anterior and posterior muscles was recorded bilaterally during forward-stepping trials. Muscle activation latencies were calculated with respect to perturbation initiation. Repeated measures ANOVAs tested for differences in muscle activation latencies between perturbation methods and body sides (anterior/posterior muscles, swing/stance limb sides); Holm-Bonferroni sequentially rejective procedure adjusted alpha during multiple comparisons. Anterior muscle activation latencies were similar between methods (∼210 ms). During PLAT trials, posterior muscles demonstrated symmetrical distal-proximal activation between 70 ms and 260 ms, bilaterally. During PULL trials, stance-limb side posterior muscles demonstrated proximal-distal activation 70–130 ms; the activation latencies (∼80 ms) were not different between the stance-limb side posterior muscles. Previous examinations of method comparisons have examined results across publications, and generally have not accounted for different stimulus characteristics. This study revealed markedly different neuromuscular organization of balance-correcting responses to two different perturbation methods that utilized, importantly, equivalent perturbation intensity. Interpretation of functional balance recovery responses requires clear understanding of the intensity and nature of the perturbation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".