Amodal completion requires more time in older adults
Bibliographic record
Abstract
In everyday settings, objects frequently partially occlude each other. Thus, amodal completion is critical for object recognition in naturalistic contexts. However, the effects of aging on amodal completion remain unexplored. Therefore, we measured the extent and time course of amodal completion for younger and older adults using a shape discrimination task in which subjects judged the orientation of a moving rectangle as horizontal or vertical (Murray, Sekuler & Bennett, 2001). Observers completed three conditions: 1) complete, with the entire outline of the rectangle visible; 2) fragmented, with corners of the rectangle deleted; and 3) occluded, resembling the fragmented condition, except with corners occluded by opaque squares. In younger observers, this task is easiest with complete stimuli and most difficult with fragmented. Performance with occluded stimuli resembles that of complete or fragmented, depending on the extent to which the observer amodally completes the rectangle behind the occluders. Specifically, Murray et al. found that the younger adults performed the complete and occluded tasks similarly at stimulus durations longer than ~60 ms. We measured thresholds for each condition at stimulus durations ranging from 15-210 ms, determining the aspect ratio that led to 70% correct. Based on initial results from 10 participants, shape discrimination is impaired for older (M=69 years) vs younger (M=23 years) adults. At the shortest durations, older observers require larger aspect ratios than younger subjects to discriminate even complete shapes accurately, and fail to reach 100% accuracy even with large aspect ratios. Performance is similar across age groups for complete shapes at longer durations. Critically, our data suggest that older adults require more time than younger adults to amodally complete occluded objects (>100 ms vs ~60 ms). We currently are investigating the result further with a larger group of subjects, to determine the time for completion in older observers more precisely. Meeting abstract presented at VSS 2017
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".