YirongMengman

Introduction

Schade, Campbell el.al have studied human pattern sensitivity for a long time.[1][2] Theories of human pattern sensitivity changed from single-resolution theories to modern multiresolution theories. Contrast sensitivity functions(CSF) are used as one of experimental measures to compare the properties of neural mechanisms and proposed theories.

The first measurement of contrast sensitivity as a function of spatial frequency was in 1956 from Schade. He asked observers to decide what contrast was necessary to just distinguish the patterns. Figure 1 was his experimental result. The horizontal axis was spatial frequency measured in terms of the display rather than cycles per degree of visual angle. The vertical axis was contrast sensitivity, that is log(1/c) where c was the contrast of the pattern of detection threshold. [1][3]

Fig. 1 : CFS Experiment result from Schade

He found that there was a drop down in sensitivity as the spatial frequency increased and there was no improvement of sensitivity at low spatial frequencies. It was also found that the contrast sensitivity function (CSF) was a product of optical and neural factors.[2] The decrease in the high spatial frequency was due to the optical blurring of the lens and the feature of retinal ganglion cells with center-surround receptive fields.[3] As for the low frequency fall off, center surround receptive field was one possible reason. Later, some researchers in neuroscience found the existence of multiple channels in vision, each of them selective to a band of spatial frequencies.[4] This finding made more and more scientists interested in measuring the CSF.

However, human vision adapts quickly to new viewing conditions. Therefore, a single CFS is not enough to describe human pattern sensitivity. By using small sinusoidal grating presented in front of observers within the middle few degrees of the visual field, researchers found that temporal properties, the mean background illuminance background level and the wavelength composition of the stimulus all had great influence on pattern sensitivity. However, if the sinusoidal grating was put on peripheral locations in the visual field, sensitivity decreased. Figure 2 showed the CSF measured at retina eccentricities of 0, 1.5, 4, 7.5, 14 and 30 degrees. [5]The observers’ peak contrast sensitivity reached nearly 100 for gratings near 5-8 cpd and could resolve gratings in about 50 cpd while observers reached limit in 2 cpd when measured in the visual periphery.

Fig. 2: CSFs with different retina eccentricity

Several neural factors could explain the deduction of absolute sensitivity and spatial resolution.The density of retinal ganglion cells drops and therefore there is less cortical area used to represent the periphery. Also, there are fewer sensors in periphery because the density of cone mosaic falls off quickly as a function of retina eccentricity. Besides, the photoreceptors in the fovea are much smaller than those in the periphery. This change of size may have something to do with the visual sensitivity as well.

Methods

We first use ISETBio[6] to generate experiment stimulus and corresponding cone mosaic response to it. The process and corresponding functions in ISETBio toolbox is described in the following figure.

Reference

[1] Otto H. Schade, "Optical and Photoelectric Analog of the Eye," J. Opt. Soc. Am. 46, 721-739 (1956)

[2] Campbell, F W, and D G Green. “Optical and retinal factors affecting visual resolution.” The Journal of physiology vol. 181,3 (1965): 576-93. doi:10.1113/jphysiol.1965.sp007784

[3] Wandell, Brian A. "Foundations of Vision" Link

[4] Campbell FW, Robson JG. Application of Fourier analysis to the visibility of gratings. J Physiol. 1968 Aug;197(3):551-66. doi: 10.1113/jphysiol.1968.sp008574. PMID: 5666169; PMCID: PMC1351748.

[5] ROVAMO, J., VIRSU, V. & NÄSÄNEN, R. Cortical magnification factor predicts the photopic contrast sensitivity of peripheral vision. Nature 271, 54–56 (1978). https://doi.org/10.1038/271054a0.

[6] Nicolas P. Cottaris, Haomiao Jiang, Xiaomao Ding, Brian A. Wandell, David H. Brainard; A computational-observer model of spatial contrast sensitivity: Effects of wave-front-based optics, cone-mosaic structure, and inference engine. Journal of Vision 2019;19(4):8. doi: 10.1167/19.4.8.