What and where: The influence of attention on visual short-term memory for item and spatial location information, and the relationship to autism traits.
Bibliographic record
Abstract
Top-down attentional control can bias visual short-term memory (VSTM), such that “retro-cues”, cues presented after a stimulus array, improve memory for cued items. Less is known, however, about whether memory for different aspects of a stimulus, such as its identity or spatial location, are also affected by top-down attention. Here we investigated the effect of top-down attention on VSTM for object type and spatial location. Further, and based on prior research suggesting a link between subthreshold autism traits and working memory impairments, we administered a questionnaire to measure autism traits. Ninety-four typical individuals varying in the number of autism traits performed a visual search task in which they were asked to detect the presence or absence of a target. To measure the top-down attention effect on VSTM, on a subset of trials, participants were probed about the target’s identity (what it was) and its location (where it was). For target-present trials, we found a dissociation in VSTM for what and where memory, as participants were less accurate for what (37%) as compared to where (86%) target information. Further, VSTM performance varied with participants’ number of autism-like traits, whereby those with fewer autism traits were more accurate for what probes and less accurate for where probes as compared to those with greater numbers of autism traits. Finally, we found that accuracy for the attention task correlated with VSTM for spatial location, but not item type. On the whole then, while participants were overall more accurate at remembering the spatial location of the target as compare to its identity, an individual’s social competence modulated this effect. In addition, top-down attention modulated VSTM for spatial information only.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".