Electrophysiological and behavioral evidence for attentional up-regulation, but not down-regulation, when encoding pictures into long-term memory
Bibliographic record
Abstract
Visual long-term memory allows us to store a virtually infinite amount of visual information (Brady, Konkle, Alvarez, & Oliva in Proceedings of the National Academy of Sciences of the United States of America, 105(38), 14325-14329, 2008; Standing in Quarterly Journal of Experimental Psychology, 25(2), 207-222, 1973). However, our ability to encode new visual information fluctuates from moment to moment. In Experiment 1, we tested the hypothesis that we have voluntary control over these periodic fluctuations in our ability to encode representations into visual long-term memory using a precueing paradigm combined with behavioral and electrophysiological indices of memory encoding. We found that visual memory encoding can be up-regulated, but it was much more difficult, if not impossible, to down-regulate encoding on a trial-by-trial basis. In Experiment 2, we tested the hypothesis that voluntary up-regulation of visual memory encoding for an item incurs a cost to memory encoding of other items by manipulating the cueing probability. Here, we found that, although the cueing benefit was constant for both low (20%) and high (50%) cueing probabilities, the benefit in the high cueing probability condition came with the overall impairment of memory encoding. Taken together, our findings demonstrate that top-down control of visual long-term memory encoding may be primarily to prioritize certain memories, but this prioritization has a cost and should not be overused to avoid its negative consequences.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".