Dynamic early adherence and late violation of Weber's law in goal-directed grasping
Bibliographic record
Abstract
An exemplar metric of goal-directed grasping (i.e., peak grip aperture) has been shown to be refractory to a psychophysical principle governing visuoperceptual estimations of object size (i.e., Weber's law: Ganel et al., 2008: Curr Biol). This dissociation suggests that vision for action and vision for perception are mediated by absolute and relative visual information, respectively. The present investigation examined whether aperture shaping elicits a unitary or time-dependent violation of Weber's law. To address this issue we asked one group of participants (i.e., perceptual task: N = 11) to provide a pantomime size estimation of differently sized objects (20, 30, 40, 50 and 60 mm of width) and had a separate group of participants (i.e., motor task: N = 16) complete goal-directed grasps of the same objects. For the perceptual task, just noticeable difference (JND) scores were computed when participants indicated that their hand opening matched the size of the target object. Importantly, motor task JNDs were computed at peak grip aperture as well as at normalized deciles of the response (i.e., 10% through 90% of grasping time). As expected, JNDs for the perceptual tasks increased with increasing target size (i.e., Weber's law). For the motor task, JNDs during the early and middle stages of the trajectory scaled to object size whereas values late in the trajectory (>50% of grasping time and including the time of peak grip aperture) did not. In other words, results for the motor task show an early, but note late, adherence to Weber's law. These results indicate that actions are not specified by a unitary and absolute visual code; rather, the time-dependent scaling of JNDs indicates a dynamic interplay between early movement programming via relative visual information and later movement control via absolute visual information.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".