Interaction between the oculomotor and postural systems during a dual-task: Compensatory reductions in head sway following visually-induced postural perturbations promote the production of accurate double-step saccades in standing human adults
Bibliographic record
Abstract
Humans routinely scan their environment for useful information using saccadic eye movements and/or coordinated movements of the eyes and other body segments such the head and the torso. Most previous eye movement studies were conducted with seated subject and showed that single saccades and sequences of saccades (e.g. double-step saccades) made to briefly flashed stimuli were equally accurate and precise. As one can easily appreciate, most gaze shifts performed daily by a given person are not produced from a seated position, but rather from a standing position either as subjects perform an action from an upright stance or as they walk from one place to another. In the experiments presented here, we developed a new dual-task paradigm in order to study the interaction between the gaze control system and the postural system. Healthy adults (n = 12) were required to both maintain balance and produce accurate single-step and double-step eye saccades from a standing position. Visually-induced changes in head sway were evoked using wide-field background stimuli that either moved in the mediolateral direction or in the anteroposterior direction. We found that, as in the seated condition, single- and double-step saccades were very precise and accurate when made from a standing position, but that a tighter control of head sway was necessary in the more complex double-step saccades condition for equivalent results to be obtained. Our perturbation results support the "common goal" hypothesis that state that if necessary, as was the case during the more complex oculomotor task, context-dependent modulations of the postural system can be triggered to reduced instability and therefore support the accomplishment of a suprapostural goal.
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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) | 0.001 | 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".