Target-distractor competition modulates saccade trajectories in space and object-space
Bibliographic record
Abstract
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, due to 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 saccade trajectories and better understand the underlying neural circuitry. For trials with short saccadic reaction times (SRTs) when target-distractor competition is still active, 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 inhibited, which resulted in saccade trajectory deviations exhibiting the effects of a spatial suppressive surround. In terms of similarity, as the target-distractor similarity decreased, the initial saccade angle shifted towards 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. Taken 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. Thus, saccade responses are more beneficial than manual responses in studies of decision-making models. Significance Statement This is the first study to determine that the distance and similarity between visual objects independently affect saccade trajectories driven by the target-distractor competition process. Thus, spatiotemporal and object identity factors separately feed into saccade planning and execution, resulting in modulations of saccade trajectory metrics which are based on spatial and object-space suppressive surround mechanisms. Furthermore, this modulation of trajectory metrics distinguishes between active and complete decision-making processes. The findings are important for understanding the dynamic networks guiding target selection and are relevant for further development of decision-making models, as well as eye-tracking applications in health and disease.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".