Probabilistic retro-cues do not determine representational state in visual working memory
Bibliographic record
Abstract
To circumvent the capacity limitations of visual working memory (VWM), mechanisms exist that govern how information is represented in memory to ensure that the most relevant information guides behaviour. Retroactively cueing an item in VWM, for instance, affects both memory quality and representational state: A retro cue that indicates with 100% validity which item will later be probed enhances memory of that item, and 'activates' its representation such that it will bias selection towards perceptually similar inputs during visual search. However, when the retro-cue is less than 100% valid (i.e., probabilistic rather than deterministic) the effect of the cue on memory performance varies with manipulations to the proportion of valid trials. Here we investigated whether probabilistic and deterministic retro-cues also differ in their influence over representational state. Participants encoded two colored squares for a subsequent memory test. Following encoding, a spatial cue indicated to participants which item was most likely to be probed at the end of the trial. Cue validity was manipulated across blocks to be either deterministic (100% valid) or probabilistic (70% valid). On a subset of trials, no memory probe was presented and the trial instead ended with a visual search task in which a colored distractor—matching either the cued memory item, the non-cued item, or neither—was presented. As expected, in the deterministic retro-cue condition, the presence of a search distractor that matched the color of the cued item reliably slowed response times relative to trials with non-matching distractors. In the probabilistic retro-cue condition, however, search response times were comparable across all three distractor conditions, despite a reliable benefit to memory performance on valid relative to invalid trials. We suggest that, while probabilistic retro-cues improve memory of the cued item, they do not bias its representational state in VWM. Meeting abstract presented at VSS 2018
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".