Returning to “inhibition of return” by dissociating long-term oculomotor IOR from short-term sensory adaptation and other nonoculomotor “inhibitory” cueing effects.
Bibliographic record
Abstract
We explored the nature and time course of effects generated by spatially uninformative peripheral cues by measuring these effects with localization responses to peripheral onsets or central arrow targets. In Experiment 1, participants made saccadic eye movements to equiprobable peripheral and central targets. At short cue-target onset asynchronies (CTOAs), responses to cued peripheral stimuli suffered from slowed responding attributable to sensory adaptation while responses to central targets were transiently facilitated, presumably due to cue-elicited oculomotor activation. At the longest CTOA, saccadic responses to central and peripheral targets were indistinguishably delayed, suggesting a common, output/decision effect (inhibition of return; IOR). In Experiment 2, we tested the hypothesis that the generation of this output effect is dependent on the activation state of the oculomotor system by forbidding eye movements and requiring keypress responses to frequent peripheral targets, while probing oculomotor behavior with saccades to infrequent central arrow targets. As predicted, saccades to central arrow targets showed neither the early facilitation nor later inhibitory effects that were robust in Experiment 1. At the long CTOA, manual responses to cued peripheral targets showed the typical delayed responses usually attributed to IOR. We recommend that this late "inhibitory" cueing effect (ICE) be distinguished from IOR because it lacks the cause (oculomotor activation) and effect (response bias) attributed to IOR when it was named by Posner, Rafal, Choate, and Vaughan (1985).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".