Hand position alters vision by biasing processing through different visual pathways
Bibliographic record
Abstract
The present study investigated the mechanisms responsible for the differences between visual processing for stimuli near and far from the hands. The idea that objects near the hands are immediate candidates for action led us to hypothesize that vision near the hands would be biased toward the action-oriented magnocellular (M) visual pathway that supports processing with high temporal resolution but low spatial resolution. Conversely, objects away from the hands are not immediate candidates for action and, therefore, would benefit from the perception-oriented parvocellular (P) visual pathway that supports processing with high spatial resolution but low temporal resolution. We tested this hypothesis using two important psychophysical correlates of the M and P pathways. Namely, we presented subjects with a spatial-gap detection task that involved high spatial frequency signals detectable by the P-cells, and a separate temporal-gap detection task which involved high temporal frequency signals detectable by the M-cells. Consistent with our prediction, we found better performance on the temporal-gap detection task and worse performance on the spatial-gap detection task for stimuli near the hands compared to the far stimuli. These findings suggest that altered visual processing near the hands may be caused by differential activation of the two visual pathways. 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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".