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To explore whether subtle changes in visual quality can be detected using different measures of visual function against the quick contrast sensitivity function test (quick CSF).Methods: Sixty participants, aged 17 to 34 years, were enrolled. Participants' vision was degraded by 0.25 D undercorrection (0.25 D), 60% neutral density filter brightness reduction (60% ND), and 0.8 Bangerter foil optical diffusion (0.8BAN). Visual function tests including visual acuity and contrast sensitivity (CSV-1000E and quick CSF) were measured with participant's best-corrected vision and under simulated visual degradation conditions. Test sensitivities in detecting differences were compared.Results: Statistically significant visual acuity degradation was observed in the 0.8BAN condition only (P corrected < 0.001). With CSV-1000E and outliers removed, significant CS degradation was observed in all spatial frequencies, area under log CSF (AULCSF) in the 0.8BAN condition (P corrected < 0.001 for all), medium and high spatial frequencies and AULCSF in the 60%ND condition (P corrected,6cpd = 0.002, P corrected,12cpd = 0.005, P corrected,18cpd = 0.001, P corrected,AULCSF < 0.001) and the 0.25 D condition (P corrected,6cpd = 0.011, P corrected,12cpd = 0.013, P corrected,18cpd = 0.015, P corrected,AULCSF < 0.001). With the quick CSF, significant CS degradation was observed in all simulated visual conditions in all spatial frequencies, cutoff frequency and AULCSF (P corrected < 0.001 for all). Test-retest reliability of the quick CSF method was high; coefficient of repeatability ranged from 0.14 to 0.18 logCS. Conclusions:Compared with visual acuity and chart-based CS tests, the quick CSF method provided more reliable and sensitive measures to detect small visual changes.Translational Relevance: The quick CSF method can provide sensitive and reliable measures to monitor disease progression and assess treatment outcomes.

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Contrast sensitivity (CS) is important when assessing functional vision. However, current techniques for assessing CS are not suitable for young children or non-verbal individuals because they require reliable, subjective perceptual reports. This study explored the feasibility of applying eye tracking technology to quantify CS as a first step toward developing a testing paradigm that will not rely on observers’ behavioral or language abilities. Using a within-subject design, 27 healthy young adults completed CS measures for three spatial frequencies with best-corrected vision and lens-induced optical blur. Monocular CS was estimated using a five-alternative, forced-choice grating detection task. Thresholds were measured using eye movement responses and conventional key-press responses. CS measured using eye movements compared well with results obtained using key-press responses [Pearson’s rbest–corrected = 0.966, P &lt; 0.001]. Good test–retest variability was evident for the eye-movement-based measures (Pearson’s r = 0.916, P &lt; 0.001) with a coefficient of repeatability of 0.377 log CS across different days. This study provides a proof of concept that eye tracking can be used to automatically record eye gaze positions and accurately quantify human spatial vision. Future work will update this paradigm by incorporating the preferential looking technique into the eye tracking methods, optimizing the CS sampling algorithm and adapting the methodology to broaden its use on infants and non-verbal individuals.

PurposeCompare peripheral contrast sensitivity functions (CSF) between myopes and emmetropes to reveal potential myogenic risks during emmetropization.Materials and methodsThis observational, cross-sectional, non-consecutive case study included data from 19 myopes (23.42 ± 4.03 years old) and 12 emmetropes (22.93 ± 2.91 years old) who underwent central and peripheral quick CSF (qCSF) measurements. Summary CSF metrics including the cut-off spatial frequency (cut-off SF), area under log CSF (AULCSF), low-, intermediate-, and high-spatial-frequency AULCSFs (l-, i-, and h-SF AULCSFs), and log CS at 19 SFs in the fovea and 15 peripheral locations (superior, inferior, temporal, and nasal quadrants at 6, 12, 18, and 24° eccentricities, excluding the physiological scotoma at 18°) were analyzed with 3-way and 4-way between-subjects analysis of variance (ANOVA) (α = 0.05).ResultsThree-way ANOVA showed that myopes had significantly increased AULCSF at 6° (mean difference, 0.08; 95% CI, 0.02–0.13; P = 0.007) and 12° (mean difference, 0.09; 95% CI, 0.03–0.14; P = 0.003). Log CS at all 19 SFs were higher in the myopia group compared to the normal group (mean differencesuperior, 0.02; 95% CI, 0.01–0.20; P = 0.02 and mean differenceinferior, 0.11; 95% CI, 0.02–0.21; P = 0.01) at 12°. The h-SF AULCSF at 6° (mean differenceinferior, 1.27; 95% CI, 0.32–2.22; P = 0.009) and i-SF AULCSF at 12° (mean differencesuperior, 5.31; 95% CI, 4.35–6.27; P &lt; 0.001; mean differenceinferior, 1.14; 95% CI, 0.19–2.10; P = 0.02) were higher in myopia vs. normal group.ConclusionWe found myopia increased contrast sensitivity in superior and inferior visual field locations at 6° parafoveal and 12° perifoveal regions of the retina. The observation of increased contrast sensitivities within the macula visual field in myopia might provide important insights for myopia control during emmetropization.