In and out of consciousness - the role of visual short-term memory
Bibliographic record
Abstract
What is involved in holding a visual object in conscious awareness? We approached this question by using a typical shape-from-motion (SFM) display, in which fragmented line-drawings of an object move relative to a background of randomly oriented lines. When static, the fragmented line-drawings are indistinguishable from the line background, but when motion is added observers can readily distinguish the figure from the ground. The resulting percept of the object persists briefly even after the motion has stopped. During this persistence period, the object fades out of consciousness as it disintegrates and blends into the background. We wanted to examine whether visual short-term memory (VSTM) is involved in sustaining the percept during the persistence period. Participants observed SFM displays that were presented bilaterally and were asked to indicate with a button press for how long the object persisted after the motion stopped. While participants performed this task, we measured their brain activity using electroencephalography (EEG). Specifically, we examined the contralateral delay activity (CDA) which is a negative ERP waveform computed as the difference between contralateral and ipsilateral activity and whose amplitude correlates with VSTM capacity. In other words, we used a neural index of VSTM to test for its involvement. We observed a greater negativity (larger CDA amplitude) for conditions that induced perceptual persistence compared to a control condition. This suggests that VSTM is involved in holding a visual object in conscious awareness.
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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 | 0.001 | 0.001 |
| 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".