Memory-guided saccades to visual stimulus sequences: influence of set-size and spatiotemporal structure on recall accuracy
Bibliographic record
Abstract
Saccades have been used extensively as a tool to measure cognitive processes such as visual working memory (VWM). The goal of this study was to identify the effect of spatiotemporal structure on performance in memory-guided saccade sequences. Six participants (ages 21-34) were presented with a sequence of targets on a 5x5 LED display encompassing 20°x20° of visual space, then they were told to fixate the central LED and memorize a sequence of 3-6 targets presented peripherally. The spatiotemporal structure of this sequence could be (1)structured (recognizable shape and temporal order), (2)semi-structured (recognizable shape with random temporal order) or (3)unstructured (random shape, random temporal order). Following offset of the fixation light, subjects saccade toward the remembered spatiotemporal sequence of targets. Presentation and execution of saccades were in complete darkness. ANOVA results showed significant main effects: 1)saccade errors were greatest for unstructured conditions and 2)targets presented earlier in sequence were recalled with higher accuracy than later targets. There were also interactions between spatiotemporal structure and 1)set-size (structure provided greater benefits for larger set-sizes) and 2)order (structure provided more benefits for early targets). However, in this experiment it was difficult to disentangle errors of target choice, errors of target position memory, and saccade motor errors. Therefore, in Experiment 2, we added a continuously-displayed placeholder array outlining the 25 possible target locations, thus providing additional allocentric cues for target selection in the recall/motor execution phase. Preliminary results (n=4) for Experiment 2 show similar trends with respect to the effect of spatiotemporal structure, however, the presence of allocentric cues seems to greatly improve the recall accuracy compared to Experiment 1. Overall, these results show that VWM capacity is improved by the presence of spatiotemporal structure for sequences that had egocentric and allocentric spatial representation, but that this interacts with other factors such as set-size. Meeting abstract presented at VSS 2018
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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 | 0.001 | 0.014 |
| 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 | 0.000 |
| 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".