Exploring the role of reduced optic flow in dynamic balance
Bibliographic record
Abstract
INTRODUCTION: When optic flow-related visual feedback is reduced to zero (no scene motion with head motion), the amplitude of postural sway increases. However, there is limited work examining the amount of optic flow required to maintain stable (or baseline) amplitudes of postural sway, especially during dynamic stance tasks where there is an increased reliance on visual cues. OBJECTIVES: The objective of the present study was to examine optic flow during dynamic stance and determine the amount of optic flow required before postural sway deviates from conditions with a gain of 1. METHODS: Twenty-six healthy adults stood on a force plate (used to calculate Centre of Pressure; COP) mounted to a motorized platform that pseudo-randomly translated continuously in the anteroposterior direction ( ± 5 cm, 0-1 Hz) for 60-s. Participants wore a virtual reality head-mounted display, used to show a virtual environment and assess head position (HeadPos). Optic flow-related visual feedback was reduced relative to head motion (0-1 in 0.25x increments). Amplitude and mean power (MP for four bands: LOW, 0-0.1 Hz; MED, 0.1-0.5 Hz; MED-HIGH, 0.5-1 Hz; HIGH, 1-5 Hz) of COP and HeadPos was used to quantify movement. RESULTS: COP and HeadPos amplitude, and MED-MP increased when optic flow gain was less than 0.5x. CONCLUSIONS: Therefore, half the amount of optic flow-related visual feedback is enough to sustain levels of postural sway observed in real-world conditions (gain of 1). Visual contributions to dynamic balance control likely extend beyond previously theorized frequencies (<0.1 Hz in quiet stance), signifying the importance of vision during complex postural tasks.
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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 | 0.001 |
| 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".