Inhibition of return: An information processing theory of its natures and significance
Bibliographic record
Abstract
Inhibition of return (IOR) is an inhibitory aftereffect of visuospatial orienting, typically resulting in slower responses to targets presented in an area that has been recently attended. Since its discovery, myriad research has sought to explain the causes and effects underlying this phenomenon. Here, we briefly summarize the history of the phenomenon, and describe the early work supporting the functional significance of IOR as a foraging facilitator. We then shine a light on the discordance in the literature with respect to mechanism—in particular the lack of theoretical constructs that can consistently explain innumerable dissociations. We then describe three diagnostics (central arrow targets, locus of slack logic and the Psychological Refractory Period, and performance in speed-accuracy space) used to support our theory that there are two forms of inhibition of return—the form which is manifest being contingent upon the activation state of the reflexive oculomotor system. The input form, which operates to decrease the salience of inputs, is generated when the reflexive oculomotor system is suppressed; the output form, which operates to bias responding, is generated when the reflexive oculomotor system is not suppressed, Then, we subjected a published data set, wherein inhibitory effects had been generated while the reflexive oculomotor system was either active or suppressed, to diffusion modelling. As we hypothesized, based on the aforementioned theory, the effects of the two forms of IOR were best accounted for by different drift diffusion parameters. The paper ends with a variety of suggestions for further research.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".