ArticleJournal of vision2020
Combining optical and neural components in physiological visual image quality metrics as functions of luminance and age.
Article in Journal of vision, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 22 citations in OpenAlex.
- The Effect of Pupil Size on Cone Contrast Sensitivity.Life (Basel, Switzerland) · 2025Article
- Defining metrics of visual acuity from theoretical models of observers.Journal of vision · 2024Article
- Structure-Function Relationship in Keratoconus: Spatial and Depth Vision.Translational vision science & technology · 2023Article
- Absolute prediction of relative changes in contrast sensitivity with aberrations using a single metric of retinal image quality.Biomedical optics express · 2023Article
- A study on disability glare vision in young adult subjects.Scientific reports · 2023Article
- Impact of temporal fluctuations in optical defocus on visual acuity: Empirical results and modeling outcomes.Journal of vision · 2023Article
- Predicting subjective refraction with dynamic retinal image quality analysis.Scientific reports · 2022Article
- Clinical applications of personalising the neural components of visual image quality metrics for individual eyes.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2022Article
- Digital ocular swept source optical coherence aberrometry.Biomedical optics express · 2021Article
- Orientation-specific long-term neural adaptation of the visual system in keratoconus.Vision research · 2021Article
- Resolution acuity across the visual field for mesopic and scotopic illumination.Journal of vision · 2020Article
Corrections and comments
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Authors and funding
4 authors at 4 institutions in 2 countries.
Funding
Abstract
Visual image quality metrics combine comprehensive descriptions of ocular optics (from wavefront error) with a measure of the neural processing of the visual system (neural contrast sensitivity). To improve the ability of these metrics to track real-world changes in visual performance and to investigate the roles and interactions of those optical and neural components in foveal visual image quality as functions of age and target luminance, models of neural contrast sensitivity were constructed from the literature as functions of (1) retinal illuminance (Trolands, td), and (2) retinal illuminance and age. These models were then incorporated into calculation of the visual Strehl ratio (VSX). Best-corrected VSX values were determined at physiological pupil sizes over target luminances of 104 to 10-3 cd/m2 for 146 eyes spanning six decades of age. Optical and neural components of the metrics interact and contribute to visual image quality in three ways. At target luminances resulting in >900 td at physiological pupil size, neural processing is constant, and only aberrations (that change as pupil size changes with luminance) affect the metric. At low mesopic luminances below where pupil size asymptotes to maximum, optics are constant (maximum pupil), and only the neural component changes with luminance. Between these two levels, both optical and neural components of the metrics are affected by changes in target luminance. The model that accounted for both retinal illuminance and age allowed VSX, termed VSX(td,a), to best track visual acuity trends (measured at 160 and 200 cd/m2) as a function of age (20s through 70s) from the literature. Best-corrected VSX(td,a) decreased by 2.24 log units between maximum and minimum target luminances in the youngest eyes and by 2.58 log units in the oldest. The decrease due to age was more gradual at high target luminances (0.70 log units) and more pronounced as target luminance decreased (1.04 log units).
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