Revaluating the Visual Short-Term Memory Benefit for 3-D Stimuli
Bibliographic record
Abstract
Given the 3-D nature of the visual environment, it is surprising that the majority of research in visual short-term memory (VSTM) has focussed on 2-D object properties. Experiments that have assessed effects of 3-D location on VSTM used sequentially presented depth planes (Xu & Nakayama, 2007, Journal of Experimental Psychology, 136, 653-662). Due to vergence eye movements, these sequential arrays were effectively presented at zero disparity. Here we use a different paradigm to evaluate the effect of distributing elements in depth on VSTM. Oriented line segments (square brackets) served as the visual stimulus to be retained in VSTM. We used a letter recall task to keep observers from rehearsing a cognitive descriptor of bracket orientation (e.g. up, down, left, right). On each trial, observers viewed a series of (3-4) letters (750ms) followed by an array of square brackets (1000ms) presented at two randomly selected orientations on each trial. In the test phase another set of letters appeared and observers indicated if they were the same or different from the first (50% of trials one letter was different). Two square brackets then appeared and again observers indicated same or different (50% of trials one item was different). Reaction time was measured for each task. There were four stimulus conditions: i) zero disparity (single plane) ii) zero disparity half density iii) two disparity-defined planes with oriented brackets randomly distributed iv) two disparity-defined planes each consisting of one orientation. Our proportion correct and d' measures show that VSTM does benefit from simultaneous distribution of elements across depth planes. However, the advantage is not due to increased sensitivity in the 3-D offset condition, but to reduced sensitivity in the single plane condition. We conclude that location binding is not the critical factor; the addition of multiple planes helps isolate features of interest, permitting efficient storage. Meeting abstract presented at VSS 2014
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".