A Reentrant View of Visual Masking, Object Substitution, and Response Priming
Bibliographic record
Abstract
Abstract When a mask follows a briefly presented target there are several consequences. Theone that has historically received the most attention is a reduction in the visibility ofthe target. This is the conventional definition of masking. Yet, another equallyimportant consequence is that errors in target identification are biased toward theidentity of the mask rather than being randomly distributed among the targetalternatives. This is evidence of object substitution. Finally, when the target is asignal to make a speeded action, this action can be influenced by a prime stimulusthat is not even visible to the participant. This is known as masked responsepriming. In this chapter we review evidence concerning all three of theseconsequences of viewing rapid visual sequences. We argue that these consequencesare difficult to understand, either individually or together, as the consequence ofstrictly feed-forward processing in the visual brain. In contrast, when these resultsare considered from the perspective of reentrant visual circuitry, they are easier tounderstand and to relate to one another. Moreover, predictions derived from areentrant view of the brain lead to unexpected and novel results that are confirmedwhen tested against psychophysical data.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".