Target–Distractor Competition Modulates Saccade Trajectories in Space and Object Space
Bibliographic record
Abstract
Saccade planning and execution can be affected by a multitude of factors present in a target selection task. Recent studies have shown that the similarity between a target and nearby distractors affects the curvature of saccade trajectories, because of target-distractor competition. To further understand the nature of this competition, we varied the distance between and the similarity of complex target and distractor objects in a delayed match-to-sample task to examine their effects on human saccade trajectories and better understand the underlying neural circuitry. For trials with short saccadic reaction times (SRTs) when target-distractor competition is still active, the distractor is attractive and saccade trajectories are deviated toward the distractor. We found a robust effect of distance consistent with saccade vector averaging, whereas the effect of similarity suggested the existence of an object-based suppressive surround. At longer SRTs, there was sufficient time for competition between the objects to complete and the distractor to be repulsive, which resulted in saccade trajectory deviations away from the distractor exhibiting the effects of a spatial suppressive surround. In terms of similarity, as the target-distractor similarity decreased, the initial saccade angle shifted toward the target, reflecting stronger distractor inhibition. There were no interactions between distance and similarity at any point in the time course of target-distractor competition. Together, saccade trajectories reflect target-distractor competition that is affected independently by both spatial and object space suppressive surrounds. The differences in saccade trajectories at short and long SRTs distinguish between active and completed decision-making processes.
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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".