Peripheral Contrast Sensitivity in Human Adults: Measurements with Gabor Sinusoids Over a Broad Range of Eccentricities
Bibliographic record
Abstract
Purpose: Contrast sensitivity (CS) is considered the most comprehensive single measure of human spatial vision. Although solid data exist for CS in the near periphery (0 to 20o), few studies have examined CS at greater eccentricities and even fewer have employed Gaussian filtered sine waves (Gabor patches) which provide both reliable measurements and relative freedom from detection artifacts. In addition to a better understanding of retinal and neural mechanisms, establishing normative CS data across a broad range of eccentricities provides help in the assessment of eye diseases which target peripheral vision (e.g. glaucoma, RP, retinal degeneration). Methods: Right eyes from 20 young adults were tested with vertically-oriented sinusoidal Gabor patches that ranged logarithmically in spatial frequency (SF) from 0.375 to 18 cy/deg and in contrast from 0.001 to 0.30. Contrast thresholds at each SF were obtained foveally and from 100 to 800 within the temporal visual field. Testing was repeated 3 to 5 times for each adult. Results: CS was highest with central vision (M (across SF) = 145.9) but declined progressively at 100 (M = 57.1), 200 (M= 37.4), 400 (M=15.3), and 600 (M= 5.6). No consistent responses were obtained at 800. Across all eccentricities, CSFs displayed the typical inverted-U shape but peak CS shifted progressively to lower SF. Repeated measurements were highly consistent across all SF (r = 0.62 to 0.85). Conclusions: CS can be measured reliably up to at least 600 in the periphery. Spatial functioning decreases by about 0.24 log units per 10o across the periphery with the rate of reduction relatively greater for higher spatial frequencies. Overall, these psychophysical data are consistent with anatomical and physiological data describing the relative ratios and efficiency of P-cells in the peripheral retina. Meeting abstract presented at VSS 2015
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".