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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".