Human ability to resolve temporal variation, or flicker, in the luminance (brightness) or chromaticity (color) of an image declines with increasing frequency and is limited, within the central visual field, to a critical flicker frequency of Ϸ50 and 25 Hz, respectively. Much remains unknown about the neural filtering that underlies this frequency-dependent attenuation of flicker sensitivity, most notably the number of filtering stages involved and their neural loci. Here we use the process of flicker adaptation, by which an observer's flicker sensitivity is attenuated after prolonged exposure to flickering lights, as a functional landmark. We show that flicker adaptation is more sensitive to high temporal frequencies than is conscious perception and that prolonged exposure to invisible flicker of either luminance or chromaticity, at frequencies above the respective critical flicker frequency, can compromise our visual sensitivity. This suggests that multiple filtering stages, distributed across retinal and cortical loci that straddle the locus for flicker adaptation, are involved in the neural filtering of high temporal frequencies by the human visual system.

Human pattern resolution is limited by optical blurring as well as neural filtering by a cascade of retinal and cortical sites with progressively lower resolution limits. Curiously, pattern structure can influence perceived color: a high-contrast, monochromatic (single wavelength) pattern appears desaturated (closer to white) relative to a uniform field of the same wavelength. Here we show that this desaturation is evident even when the pattern's frequency is too high for conscious perception, implicating a nonlinear process--namely light adaptation--at the level of single cone photoreceptors. We propose a neural mechanism in which fast, involuntary eye movements serve to shift control over perception between two competing cone populations, each operating at different levels of adaptation.

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Abnormal rod-receptor activity can be quantitatively assessed in humans by fitting a computational model of the rod's response to the leading edge of the a wave of the electroretinogram. One purpose of the present study was to compare two procedures for fitting the model to the electroretinogram. A computationally simpler method gives comparable results to the more labor-intensive method used previously. This finding holds for both normal observers and patients with retinodegenerative disease that affects the receptors unevenly. A second purpose of the present study was to consider the effects of a heterogeneous disease process on the parameters of the model. a waves from a heterogeneous retina are computer simulated and are fitted with the receptor model. This analysis suggests that the model will overestimate the change in the healthiest rods and will underestimate the percentage of the rods that are significantly affected.

Since the Naka-Rushton eq was first shown to fit the change in trouh-to-peak b-wave amplitude with flash intensity1,2, it has been fitted to b-wave data from a large number of patients. The parameters estimated from these fits, the semisaturation intensity (K) and the maximum response (Vmax) are affected in different ways by different diseases. Fig. 1, from Birch et a13, shows the deviations from the normal parameters for 41 patients with cone-rod dystrophy (CRD) or autosomal dominant retinitis pigmentosa (ADRP) retaining measurable rod ERGs. Each data point represents an individual patient and shows the change in log K and the change in log Vmax from the log of the mean normal. Typical of diseases of the receptors, these patients show large changes