Voluntary action decreases spatial perception in central and peripheral vision
Bibliographic record
Abstract
The spatial perception of a visual stimulus is optimal at the fovea and diminishes with increasing eccentricity (Brown et al., 2005). As well, visual perception has also been shown to be modulated during a voluntary movement. For example, temporal visual events are less susceptible to accompanying auditory cues during movements (Tremblay and Nguyen, 2010) while spatial cues are more poorly perceived at peak-limb velocity (Hajj et al., 2019). However, visual stimuli in these studies were presented below and at the fovea, respectively, which may explain the discrepant results for temporal vs. spatial perception. The purpose of this study was to investigate how visual spatial processing differs in peripheral vs. central vision at peak-limb velocity. Participants (n=12) performed an inspection time (IT) task whereby they identified the longest side of a briefly presented (25-150 ms) asymmetrical pi figure. In the no-movement condition, the IT task occurred in central (1deg) and peripheral (15deg) vision while participants grasped a manipulandum. In the movement condition, the IT stimulus appeared at and below the foveated target at peak-limb velocity of a rapid 30deg elbow extension to a target. While IT task performance was significantly poorer in the peripheral field, visual spatial processing was further diminished at peak velocity in both peripheral and central vision. These findings indicate that changes in temporal visual event perception during voluntary action (Tremblay and Nguyen, 2010) are accompanied by decreased spatial perception of visual stimuli at peak-limb velocity both at the fovea and at 15deg of visual eccentricity.Acknowledgments: University of Toronto, Natural Sciences and Engineering Research Council of Canada (NSERC)
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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 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".