Rhythmical eye-head-torso rotation alters fore-aft head stabilization during treadmill locomotion in humans*
Bibliographic record
Abstract
A repetitive manoeuvre called torso rotation (TR) is known to temporarily reduce the gain of the horizontal vestibulo-ocular reflex by 10-15% in healthy humans. TR consists of a series of rhythmical rotations of the eyes, head and upper body executed continuously for 30 minutes while standing. Our aim was to investigate whether TR affects the ability to hold the head in a fixed fore-aft position relative to space while walking on a treadmill with eyes closed. Ten healthy subjects stood in a carefully standardized position on a stationary treadmill. The treadmill started unexpectedly and ran for 4 s at 29 cm/s. The test stimulus was a linear acceleration in the fore-aft direction at the moment of treadmill start-up. Linear head position (i.e., ability to stabilize the head) was measured during and following the stimulus. A mechanical system prevented head rotation. Two series of 60 trials were performed before TR (control 1 and control 2 series) and one after TR. Before TR, subjects drifted rearward at an average drift velocity +/- S.D. = 3.1 +/- 0.9 cm/s. This drift was reasonably stable over time within and between the two control series. After TR, head holding ability was further impaired, with subjects having more difficulty to stabilize their head after treadmill start-up. In the first 10 trials after the arrest of TR, the average drift velocity was significantly larger than before TR(6.1 +/- 1.5 cm/sec, p < 0.01). Recovery to control values followed a roughly exponential time course, with 67% recovery occurring in the first 3.4 minutes after TR. Our results indicate that TR impairs the ability to sense and/or respond to fore-aft linear accelerations of the head following treadmill start-up in the absence of vision.
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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".