The effect of noise on motion binding is similar in younger and older adults
Bibliographic record
Abstract
The level of internal noise affecting motion processing is higher in older than younger adults (Bennett et al., Vision Res, 2007; Bocheva et al., Exp Brain Res, 2013). Normally, higher noise is associated with poorer performance; however, Lorenceau(Vision Res, 1996) showed that visual stimulus noise sometimes can help perception. In Lorenceau's task, a square stimulus composed of dots (5/side) maintained a fixed orientation while rotating around central fixation. The square's rotation was decomposed into two sinusoidal components corresponding to the motion of the horizontal and vertical lines. Critically, the corners of the square were removed, so participants had to combine the two motion components to discriminate the global rotation (clockwise or counter-clockwise). Lorenceau found that motion binding was easier when noise was added to the individual dots forming the square. Here we asked whether age-related changes in internal noise would affect perception, with seniors potentially requiring less external noise to perceive the global motion. We tested younger (19-27 years; N=6) and older (64-75 years; N=6) adults using Lorenceau's stimulus displayed for 4 durations (150ms, 300ms, 600ms, 1200ms) at 3 levels of external noise (0.0002, 0.027, 0.081). In general, we found a similar pattern of results as Lorenceau, with better performance at higher levels of noise, but the effect of the noise depended on stimulus duration. At 150ms, there was no difference across noise levels for younger or older adults. As trial durations increased, performance increased in the moderate and high noise conditions, and decreased in the low noise condition. A similar overall pattern was observed for both age groups, although maximum performance differed numerically, but not significantly, for older (~85%) versus younger (~95%) observers. Additional studies are examining whether clearer age-related effects are seen at more extreme noise levels, and whether seniors might benefit from even longer stimulus durations. 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".