The spatial location of remote distractors differentially influence the planning times of pro- and antisaccades
Bibliographic record
Abstract
A visual distractor located contralateral to a target stimulus or within central vision influences the planning times of stimulus-driven prosaccades (i.e., the remote distractor effect; RDE). Some evidence suggests that the RDE arises from the retinotopic organization of the motor map in the superior colliculus and the competition between stimulus-specific saccade neuron populations. To date however, research has not addressed whether the RDE influences the programming of antisaccades. Indeed, such an issue represents an important area of inquiry because it provides a basis for determining whether the RDE manifests as a function of the spatial properties of a stimulus or the location of a required response. As such, the present investigation had participants complete pro- and antisaccades to briefly presented (i.e., 50 ms) proximal (4°) and distal (8°) target stimuli (i.e., ‘x’) located left and right of central fixation. Importantly, pro- and antisaccades were performed in conditions wherein a distractor (i.e., ‘o’) concurrently appeared at central fixation, or contralateral, or ipsilateral to the target stimulus. As well, pro- and antisaccades were performed in a distractor-free condition. In line with previous work, prosaccade reaction times (RT) were longer when a distractor was located contralateral to a target stimulus or within central vision. In contrast, antisaccade RTs were increased regardless of the spatial location of the distractor. Thus, results suggest that the top-down control of antisaccades results in a location-independent integration of the relational properties of a target and distractor and that the spatial properties of a stimulus influence extant planning times. Acknowledgments: Natural Sciences and Engineering Research Council of Canada; Major Academic Development Fund from the University of Western Ontario
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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 | 0.001 |
| 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) | 0.002 | 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".