Investigating the effects of perceptual complexity versus conceptual meaning on the neural correlates of visual working memory
Bibliographic record
Abstract
Previous research has demonstrated greater visual working memory (VWM) performance for real-world objects compared to simple features. Greater amplitudes of the contralateral delay activity (CDA) have also been noted for meaningful stimuli, despite being typically thought of as a neural marker of a fixed working memory capacity. It remains unclear whether this increased CDA amplitude is due to objects’ perceptual complexity (number of features) or conceptual meaning (semantics). Subjects performed a lateralized VWM task in which three items were presented for 1000ms, followed by a 700ms delay. Subjects then performed a two-alternative forced choice task (2AFC), to identify which of the probe images appeared in a cued location in the array. The CDA was measured over posterior channels (1300-1700ms post-stimulus onset), with behavioural performance estimated as K=N(2p-1). Stimuli were colours, real-world (intact) objects, or diffeomorphed (scrambled) real-world objects. Computational modelling suggests that diffeomorphing maintains low-level perceptual features of the objects. Thus, conceptual meaning was manipulated while controlling for perceptual complexity, as both object sets had similar visual complexity whereas only intact recognizable objects had semantic information. All 2AFC pairings were maximally dissimilar. Colours were separated by 180°, and pairs for both object conditions were determined by computational models of dissimilarity, as in Brady & Störmer (2020). Behavioural results revealed significantly better performance within-subjects (N = 15) for intact relative to scrambled objects and colours, with no difference between colours and scrambled objects. Both intact and scrambled objects had significantly larger CDA amplitudes than colours, with no difference between object conditions. Overall, behavioural findings suggest that the object benefit is driven by conceptual meaning. Critically, results also provide insight into the nature of the CDA and its role in mediating VWM storage, as similarities in neural data between object conditions suggest that the CDA may also be affected by perceptual complexity.
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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 | 0.002 |
| 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) | 0.002 | 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".