The effects of aging on surround modulation of backward contrast masking
Bibliographic record
Abstract
Saarela and Herzog (J Vis, 2008, 8(3):23, 1-10) measured backward masking for a centrally-viewed Gabor target that was produced by a small central mask that overlapped the target, a surround annulus mask, and a large combination mask (i.e., centre plus surround). Interestingly, they found that significantly less masking was produced by the combined mask than the central mask, even though the surround mask produced little masking on its own. One interpretation of this result is that the surround reduced the effectiveness of the central mask. The current study examined whether this non-linear interaction between centre and surround masks is affected by aging. Detection thresholds were measured for a Gabor target (duration=80 ms) in five younger (∼25 years) and older (∼69 years) subjects. The target was preceded or followed by surround, central, or combination masks. Thresholds were measured using surround, central, and combination masks that were displayed for 200 ms at five SOAs relative to target onset. The target and masks were 4 cpd and had a horizontal orientation. Mask contrast was 0.4; a baseline, no-mask condition also was included. Significant masking was obtained in both age groups, and the combined mask produced less masking than the central mask. However, the temporal pattern of masking across target-mask SOA differed noticeably between groups. Our results suggest strong centre-surround interactions exist in older subjects, but that the temporal properties of these interactions change with age.
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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 | 0.000 |
| 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".