The spatially asymmetric cost of memory load on visual perception: Transient stimulus-centered neglect.
Bibliographic record
Abstract
Recent evidence suggests that visual working memory (VWM) load reduces performance accuracy on a concurrent visual recognition task, particularly for objects presented in the left hemifield. It has also been shown that high VWM load causes suppression of activity in the right temporoparietal junction (TPJ). Given the resemblance of VWM load effects to symptoms of unilateral neglect (i.e., impaired perception on the left side and lesion to the right TPJ), we investigated whether VWM load effects are restricted to the left side of space or extend to object-centered reference frames. In other words, akin to object-centered neglect, can high VWM load cause a perceptual cost in attending to the left side of the stimulus? We addressed this question using an object recognition task (Experiment 1) and a visual search task (Experiment 2) showing that this transient left-neglect can indeed be modulated by an object-centered frame of reference. These findings suggest that load-induced impairments of visual attention are spatially asymmetric and can emerge within multiple spatial reference frames. Therefore, the attentional consequences of high VWM load on conscious perception may serve as a useful model of unilateral perceptual neglect.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".