The remote distractor effect for antipointing: The proximity of a distractor relative to movement-related goals influences response planning
Bibliographic record
Abstract
An extensive literature has examined how the spatial nature of a distractor (i.e., proximal vs. distal) relative to a target influences the planning of goal-directed movements with direct stimulus-response (SR) relations (i.e., prosaccade and propointing). To our knowledge, however, no work has examined how the spatial location of a distractor influences the planning of an antipointing response; that is, a reaching movement directed 180° mirror-symmetrical to the location of a target stimulus. Indeed, such a question represents an important issue in the visuomotor control literature because it provides a basis for determining whether the sensory- and/or motor-related features of a distractor influence response planning. To that end, participants completed pro- and antipointing movements in a condition that entailed a single and briefly presented target (i.e., control condition), and conditions wherein the target was presented concurrently with a proximal (i.e., ipsilateral) or distal (i.e., contralateral) distractor. Results for pro- and antipointing showed that proximal and distal distractor types produced shorter and longer RTs than the control condition, respectively. Based on these findings, we propose that the spatial relations between a distractor and movement-related goals for antipointing elicits an inhibition of visuomotor planning mechanisms. Further, we propose that distractor interference in pro- and antipointing planning emerges when participants have to select between target and non-target stimuli that code for directionally alternative motor responses. Acknowledgments: Natural Sciences and Engineering Research Council of Canada (NSERC); Academic Development Fund and Faculty Scholar Awards from the University of Western Ontario
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".