Action Rules: Why the Visual Control of Reaching and Grasping is Not Always Influenced by Perceptual Illusions
Bibliographic record
Abstract
It is generally accepted that vision first evolved for the distal control of movement and that perception or 'representational' vision emerged much later. Vision-for-action operates in real time and uses egocentric frames of reference and the real metrics of the world. Vision-for-perception can operate over longer time scales and is much more scene-based in its computations. These differences in the timing and metrics of the two systems have been examined in experiments that have looked at the way in which each system deals with visual illusions. Although controversial, the consensus is that actions such as grasping and reaching are often unaffected by high-level pictorial illusions, which by definition affect percetion. However, recent experiments have shown that, for actions to escape the effects of such illusions, they must be highly practiced actions, preferably with the right hand, and must be directed in real time at visible targets. This latter finding suggests that some of the critical components of the encapsulated (bottom-up) systems that mediate the visual control of skilled reaching and grasping movements are lateralised to the left hemisphere.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".