The effect of aging on directional tuning when making judgments about horizontal and vertical motion
Bibliographic record
Abstract
Motion direction identification is impaired in older subjects (Bennett et al., Vis Res, 2007). One explanation for this effect is that the bandwidth of directionally selective mechanisms broadens with age. Although neurophysiological work with senescent primates has found evidence of broader directional tuning in V1 neurons, it is not known if directional tuning changes similarly as a function of age in human observers. To investigate this issue, we measured direction discrimination thresholds in six younger and six older adults. The stimuli were random dot kinematograms (RDK; 400 dots), and the dependent variable was the percentage of coherently moving dots needed to discriminate left-right or up-down motion. RDKs were embedded in a mask consisting of 100 dots moving coherently in four directions: d ± δ deg and (d + 180) ± δ deg, where d is the target direction and δ is the difference between target and mask directions. For both left-right and up-down target motion, thresholds in both age groups declined monotonically as δ increased from 5 to 90 deg. For left-right target motion, neither the slope of the masking function nor threshold in a no-mask baseline condition differed between age groups. For up-down target motion, the masking function obtained with older subjects had a slope that was one-half of the slope obtained with younger subjects, and threshold in the no-mask condition was, on average, twice as high in older than younger subjects. These preliminary results are inconsistent with the idea that there is a non-specific decrease in the selectivity of directionally-tuned mechanisms with age. They suggest, instead, that the effect of aging on the selectivity of directional masking may vary with the target direction. Currently we are replicating this result on a larger sample of subjects, and generalizing it to different dot densities and speeds.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".