Practice Reduces the Effect of a Ponzo Illusion on Precision Grasping but not Manual Estimation
Bibliographic record
Abstract
Most studies of pictorial illusions rely on session-wise averages – an approach that assumes that effects of interest remain constant across successive iterations of the response within a test session. Recent evidence, however, suggests that this assumption is not always justified. For example, our group has shown that the illusory influence of the Ponzo display on the apparent size of objects is mitigated with practice for ‘awkward’ grasps executed with the ring finger and the thumb of the right (dominant) hand over the course of three consecutive days of testing, but not for awkward grasps executed with the left (non-dominant) hand (Gonzalez et al., 2008). Notably, substantial within-session reductions in the illusory effects were observed for grasps executed with the right hand. Could mechanisms underlying the within-session reduction in illusory effect extend to ‘precision’ grasps executed with the thumb and forefinger? To answer this question, we asked participants to manually estimate the length of single targets with their thumb and finger aperture a matching amount or to grasp them in a blocked ABA design. In both tasks, participants’ responses were correlated, with equal sensitivity, to target length, but only manual estimates remained consistently biased by the illusion. In contrast, the illusory effect on grasps decreased linearly over the course of testing. The consistency of the effect of the illusion across manual estimates cannot easily be attributed to a lack of haptic feedback, since the manual estimates of an additional group of participants were consistently affected despite picking up the same target immediately following each estimate. We offer three possible explanations that can account for our findings: low-level motor calibration, motor learning, and another that invokes cognitive or attentional set-shifting – a process through which the saliency of stimulus and task features is updated following a switch in task demands. Meeting abstract presented at VSS 2012
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".