Exploring the Relationship between Long-Term Memory and Attention through Attentional Templates
Bibliographic record
Abstract
It is assumed that the contents of visual working memory (VWM) guide attention. This notion has been challenged by work which has demonstrated that multiple searches for the same target changes contralateral delay activity (CDA), an event-related potential that is the putative marker of the amount of information maintained in VWM. It has been suggested that the disappearance of the CDA with an invariable target marks the transfer of the attentional template from VWM storage to long-term memory (LTM) storage. Therefore, LTM may guide attention in many situations where it has previously been assumed that VWM guides attention. However, while the transfer of attentional template from VWM to LTM is demonstrated through a decrease in the amplitude of the CDA, this shift has not been accompanied by a corresponding behavioral change in response times. The purpose of the present study was to test the hypothesis that a LTM template leads to faster performance than a VWM template (the LTM template hypothesis). Two experiments were conducted to explore this hypothesis. In Experiment 1, the LTM template hypothesis was examined by comparing performance between two different groups of subjects: the first group searched for a target that changed on every trial (variable) while the second group searched for a target that was invariable across trials. In Experiment 2, one group of subjects searched for both the variable and invariable targets. The results showed that a LTM template (invariable target search) leads to faster performance than a VWM template (variable target search). Roughly six times as many trials were required for an effect on performance compared to the number of trials required for an effect in CDA amplitude. Eye tracking results suggest the change in performance is due to more efficient search initiation and target verification.
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".