Eye-hand Coordination in Reaching and Grasping Vertically Translating Targets
Bibliographic record
Abstract
Previous research in our lab has revealed a strong visual bias toward the eventual index finger contact location when grasping stationary or horizontally moving targets. However, the unique properties of the thumb may have an increased role when grasping vertically moving targets. Using their index finger and thumb, right-handed individuals reached for and grasped 2-D rectangular targets moving upward or downward on a vertically oriented computer screen. It was expected that fixations would be directed toward the index finger when grasping upward moving targets, and to the thumb when grasping downward moving targets. In trials involving upward moving targets, initial fixations were positioned well above the target, in anticipation of the eventual movement, and remained above the target even after the target started to move. Gaze shifted to the leading (upper) edge of the target when participants initiated their reaching movement, suggesting that participants were primarily attending to the eventual contact location of the index finger. Initial fixations toward downward moving targets were positioned well below its bottom edge, once again anticipating eventual movement. When the targets started to move, gaze shifted upward to a position just below the target’s centre of mass (COM) and remained there during reach onset. Final fixations for both upward and downward moving targets were positioned slightly above the target’s COM, a location that would allow the monitoring of both index and thumb when grasping. These results suggest that while index finger placement is prioritized when grasping upward moving targets, visual attention is directed toward more central locations when grasping downward moving targets, thus allowing both contact points to be monitored simultaneously. This is suggestive of an increased importance of the thumb, in addition to the index finger placement, not shown previously when grasping stationary or horizontally translating targets.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".