A Significant Bilateral Field Advantage for Shapes Defined by Static and Motion Cues
Bibliographic record
Abstract
Matching performance is better when pairs of visual stimuli are presented in bilateral conditions--in which one stimulus is presented to each side of the visual field--than in unilateral presentations-when both stimuli are presented to one side of the field. This is called the bilateral field advantage (BFA). The processing of visual motion has also been found to be more strongly integrated across the cerebral hemispheres than is processing of static cues. However, in these studies higher-order motion tasks, such as processing motion-defined form, have not been examined. To determine if the BFA generalises to such tasks, we measured the magnitude of the effect using a shape-matching task in which the stimuli were random polygons that were either in motion, motion-defined, or static. The polygon pairs were presented either: (i) bilaterally, one to either side of the vertical meridian; (ii) unilaterally, both to one side of the vertical meridian (left or right visual fields); or (iii) centrally, vertically separated across the horizontal meridian (a control condition). An equal advantage of bilateral conditions over unilateral ones was found for all three types of polygon shape cues, showing that the BFA generalises to conditions where shapes are in motion and where shape is defined by motion. These findings are compatible with the notion that motion processing is strongly integrated across the cerebral hemispheres, and with the idea that this integration manifests itself with simple motion information, rather than with higher-order motion processing such as matching shapes defined by motion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".