Investigating the Temporal Dynamics of LTM-to-VWM Reinstatement During Visual Search
Bibliographic record
Abstract
When observers are shown a visual target to later search for, they form an attentional template—¬a mental representation of the target’s features. This template acts as a guide, allowing only stimuli that match the target’s features to capture attention. Recent research has shown that templates stored in visual working memory (VWM) do not only reflect the target object that was shown to the observer, but also features from long-term memory (LTM) that were previously associated with that object. For example, if a shape was previously associated with a specific colour, that association can be retrieved and represented in VWM, even in the absence of direct visual input: a process termed LTM reinstatement. Interestingly, reinstated features in VWM can prefentially capture attention even when they are task irrelevant. How long do you need to see an object for task-irrelevant features from LTM to be reinstated, and how long do you need to actively maintain that feature in VWM to see the attentional effects? To investigate both questions, participants memorized a set of objects with specific colours and then completed a search task where they were instructed to search for one of the memorized objects’ shapes in any colour. We manipulated how long participants saw the search target object (Exp 1) and how long they had to hold the target in VWM before the search task started (Exp 2). We found that participants needed to see the object for a minimum of about 50ms, and then maintain it in VWM for another 50ms, for LTM reinstatement to later occur. These results highlight the rapid interaction between LTM and VWM, suggesting that even brief perceptual exposure and VWM maintenance can trigger the reinstatement of task-irrelevant features.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".