Attentional Effect in Motion-Induced Position Shift
Bibliographic record
Abstract
A moving bar shifts the perceived position of a nearby flash. This effect is strongly asymmetrical: a flash at or ahead of the bar is pushed further ahead in the direction of motion but a flash behind the bar shows little or no shift in the opposite direction (Shams-Ahmar et al., ECVP 2022). Recently, it has been proposed that attentional repulsion (Suzuki & Cavanagh, JEP:HPP 1997) may cause the shift (Shams et al., ECVP 2023) as attention leads a moving bar (Szinte et al., J Neurophysiol. 2014). Here, we manipulate the expected motion direction to see if an attentional manipulation influences the motion-induced position shift. A shape moved downward to the center of the screen, where the dot flashed on top of it and the shape then moved away either rightward or leftward. In three sessions run on separate days, the probability of the second motion direction was left and right equally often, left more likely, or right more likely. We found that the illusory shift of the flash was consistently in the direction of the motion that followed it, and that the likelihood of the direction significantly affected the induced position shift (Friedman test: p=0.001; medians: unlikely=0.07 dva; ‘equally likely’=0.11 dva; likely=0.23 dva). Further, within each session, despite participants being aware of the more likely direction, the bias towards the more likely direction increased systematically across trials consistent with the notion of a gradual drift of attentional resources towards the expected direction of motion. No trial-to-trial effects were found, ruling out any contribution of serial dependence. We attribute the effects of direction frequency to a greater allocation of attention to the more frequent direction, increasing its effect on the shift. Attentional repulsion remains a viable explanation for the motion-induced shifts seen in static flashed tests.
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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 | 0.004 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".