Does attentional capture guide the contents of visual short-term memory?
Bibliographic record
Abstract
Visual short-term memory allows information within a visual scene to be encoded as an internal representation and actively maintained over time. Because this memory system is capacity limited, however, only a subset of the objects within a visual scene can be encoded in this way. In the present research, we investigated whether the objects that are selected for memory are determined solely volitionally, or whether stimulus-driven attentional capture can bias this selection. Subjects were presented an array of visual objects and asked to remember a subset of them (i.e., their volitional goal). In addition, an irrelevant distractor was used to randomly cue locations within this array (i.e., a stimulus-driven signal). Memory performance was biased by the task-irrelevant distractor, suggesting that attentional capture does guide the contents of visual short-term memory. This finding is discussed within the context of the contingency of attentional capture on top-down control settings, and in terms of the time course of the interaction between top-down volitional attention and bottom-up attentional capture.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".