Motor cost affects the decision of when to shift gaze for guiding movement
Bibliographic record
Abstract
Frequent gait modifications are often required to navigate our world. These can involve long or wide steps or changes in direction. People generally prefer to minimize the motor cost (or effort) of a movement, although with changes in gait this is not always possible. The decision of when and where to shift gaze is critical for controlling motor actions, since vision informs the brain about the available choices for movement—in this case, where to step. Here we asked how motor cost influences the allocation of gaze. To address this, we had participants walk and step to the center of sequential targets on the ground. We manipulated the motor cost associated with controlling foot placement by varying the location of one target in the lateral direction on a trial-to-trial basis within environments with different numbers of targets. Costlier steps caused a switch from a gaze strategy of planning future steps to one favoring visual feedback of the current foot placement when participants had to negotiate another target immediately after. Specifically, costlier steps delayed gaze shifts away from the manipulated target. We show that this relates to the cost of moving the leg and redirecting the body’s center of mass from target to target. Overall, our results suggest that temporal gaze decisions are affected by motor costs associated with step-to-step demands of the environment. Moreover, they provide insight into what affects the coordination between the eyes and feet for the control of stable and accurate foot placement while walking. NEW & NOTEWORTHY Changes in gait allow us to navigate our world. For instance, one may step long or wide to avoid a spilled drink. The brain can direct gaze to gather relevant information for making these types of motor decisions; however, the factors affecting gaze allocation in natural behaviors are poorly understood. We show how the motor cost associated with a step influences the decision of when to redirect gaze to ensure accurate foot placement while walking.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".