Contrast (vision)

About: Contrast (vision) is a research topic. Over the lifetime, 10379 publications have been published within this topic receiving 221480 citations.

Metrics of retinal image quality predict visual performance in eyes with 20/17 or better visual acuity

Abstract: Purpose. The purpose of this study is to determine the ability of single-value metrics of retinal image quality of the eye to predict visual performance as measured by high (HC) and low (LC) -contrast acuity at photopic (P) and mesopic (M) light levels in eyes with 20/17 and better visual acuity. Methods. Forty-nine normal subjects in good health ranging in age from 21.8 to 62.6 with 20/17 or better monocular high-contrast logarithm of the minimum angle of resolution (logMAR) acuity served as subjects. Wavefront error through the 10th Zernike radial order over a 7-mm pupil was measured on each test eye using a custom-built Shack/Hartmann wavefront sensor. For each eye, 31 different single-value retinal image quality metrics were calculated. Visual acuity was measured using HC (95%) and LC (11%) logMAR at photopic (270 cd/m 2 ) and mesopic (0.75 cd/m 2 ) light levels. To determine the ability of each metric of retinal image quality to predict each type of logMAR acuity (P HC, P LC, M HC, and M LC), each acuity measure was regressed against each optical quality metric. Results. The ability of the metrics of retinal image quality to predict logMAR acuity improved as luminance and/or contrast is lowered. The best retinal image quality metric (logPFSc) accounted for 2.6%, 15.1%, 27.6%, and 40.0% of the variance in P HC, P LC, M HC, and M LC logMAR acuity, respectively. Conclusions. In eyes with 20/17 and better P HC acuity, P HC logMAR acuity is insensitive to variations in retinal image quality compared with M LC logMAR acuity. Retinal image quality becomes increasingly predictive of logMAR acuity as contrast and/or luminance is decreased. Everyday life requires individuals to function over a large range of contrast and luminance levels. Clinically, the impact of retinal image quality as a function of luminance and contrast is readily measurable in a time-efficient manner with M LC logMAR acuity charts. (Optom Vis Sci 2006;83:635–640)

Linking visual response properties in the superior colliculus to saccade behavior.

Abstract: Here we examined the influence of the visual response in the superior colliculus (SC) (an oculomotor control structure integrating sensory, motor and cognitive signals) on the development of the motor command that drives saccadic eye movements in monkeys. We varied stimulus luminance to alter the timing and magnitude of visual responses in the SC and examined how these changes correlated with resulting saccade behavior. Increasing target luminance resulted in multiple modulations of the visual response, including increased magnitude and decreased response onset latency. These signal modulations correlated strongly with changes in saccade latency and metrics, indicating that these signal properties carry through to the neural computations that determine when, where and how fast the eyes will move. Thus, components of the earliest part of the visual response in the SC provide important building blocks for the neural basis of the sensory-motor transformation, highlighting a critical link between the properties of the visual response and saccade behavior.

The human eye as an optical filter

Abstract: The properties of the image-forming elements of the human eye are compared with the properties of the retina-brain system by considering them as two linear optical filters in cascade. The contrast sensitivity of the complete system is measured at a number of spatial frequencies by generating grating patterns of variable contrast and spatial frequency on an oscilloscope. Similar gratings are generated directly on the retina by means of Thomas Young interference, using a neon-helium laser as a coherent light source. In this manner the effect of the eye's dioptrics are bypassed. The quality of the image formed on the retina may then be determined from these two sets of measurements. The effect of pupil size on the quality of the retinal image is described to illustrate an application of the technique.