Quantifying the Functional Relationship Between Visual Acuity and Contrast Sensitivity Function

被引:1
作者
Lu, Zhong-Lin [1 ,2 ,3 ,4 ]
Zhao, Yukai [2 ]
Lesmes, Luis Andres [5 ]
Dorr, Michael [5 ]
机构
[1] NYU Shanghai, Div Arts & Sci, Shanghai, Peoples R China
[2] NYU, Ctr Neural Sci, New York, NY USA
[3] NYU, Dept Psychol, New York, NY USA
[4] NYU ECNU Inst Brain & Cognit Neurosci, Shanghai, Peoples R China
[5] Adapt Sensory Technol Inc, San Diego, CA USA
关键词
contrast sensitivity function; visual acuity; contrast sensitivity acuity; computational modeling; RIDGE-REGRESSION; FREQUENCY-CHARACTERISTICS; TUMBLING-E; VISION; REQUIREMENTS; IMPAIRMENT; MODEL; LIFE; AGE;
D O I
10.1167/iovs.65.12.33
中图分类号
R77 [眼科学];
学科分类号
100212 ;
摘要
PURPOSE. Studies have reported that individuals with certain ocular disorders may have significant decreases in contrast sensitivity function (CSF) despite having normal or near normal visual acuity (VA). This study seeks to elucidate this phenomenon by investigating the relationship between VA and CSF. METHODS. We analyzed data from 14 eyes tested with Electronic Early Treatment Diabetic Retinopathy and quantitative CSF under four Bangerter foil conditions (n = 56). From the CSF data, we estimated peak gain, peak frequency, and contrast sensitivity acuity (CSA). We explored the correlations between VA and various CSF parameters and evaluated five predictive models of VA using CSA alone and in combination with additional CSF parameters through ridge regression. RESULTS. We found that similar VA scores can correspond with markedly different CSFs and observed significant correlations among all CSF parameters and between VA and each CSF parameter (all P < 0.001). The most effective predictive model, incorporating CSA and peak gain, explained 90.97% of the variance with a root mean squared error of 0.0676 logMAR, which is comparable with the average standard deviation of the VA scores (0.0627 logMAR) and accounted for 38.6% of the residual variance not explained by the CSA-alone model. CONCLUSIONS. This study offers the first empirical inference of the quantitative relationship between VA and CSF, suggesting that various CSF parameter combinations can yield identical VA. This might help to explain why some clinical populations with normal or near-normal VA exhibit significant CSF deficits and calls for further research in different clinical settings. computational modeling
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页数:11
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