The impact of binocular disparity on visual short-term memory
Bibliographic record
Abstract
Although visual short-term memory (VSTM) has been studied extensively, the majority of this literature has focused on the impact of 2-D stimulus properties. Studies of the effects of binocular disparity on VSTM have drawn conflicting conclusions due to design and stimulus differences. To reassess the impact of stereopsis on VSTM we used a novel paradigm in which oriented brackets were presented on two disparity-defined planes simultaneously. A concurrent letter recall task prevented observers from cognitively rehearsing a verbal descriptor of the brackets. On each trial, observers viewed a set of four randomly selected letters, followed by a field of brackets containing two of four possible orientations (left, right, up, down). Observers were asked to remember the set of letters, and the bracket orientations. In the test phase, another set of letters appeared and observers indicated if they were the same or different from the first. A field of brackets then appeared and observers indicated if the orientations were the same or different from the original. We computed d’ for four conditions: zero disparity full-density, zero disparity half-density, two disparity-defined planes with non-uniformly distributed brackets and two disparity-defined planes with uniformly distributed brackets (each plane contained one orientation). We found no difference between 2-D and 3-D conditions, however there was a large effect of element distribution in the 3-D conditions. In a follow up experiment we varied binocular disparity to determine whether this result was specific to a particular depth offset. There was a clear interaction between disparity and element distribution in the 3-D conditions. We conclude that there is no overall benefit to VSTM of displacing stimuli on different depth planes. Instead it appears that VSTM is influenced by the perceptual organization of the elements, which can be influenced by their 3-D placement. Meeting abstract presented at VSS 2015
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".