It is possible to discriminate between grating contrasts over a 300-fold contrast range, whereas V1 neurons have very limited dynamic ranges. Using populations of model neurons with contrast-response parameters taken from electrophysiological studies (cat and macaque), we investigated ways of combining responses to code contrast over the full range. One model implemented a pooling rule that retained information about individual response patterns. The second summed responses indiscriminately. We measured accuracy of contrast identification over a wide range of contrasts and found the first model to be more accurate; the mutual information between actual and estimated contrast was also greatest for this model. The accuracy peak for the population of cat neurons coincided with the peak of the distribution of contrasts in natural images, suggesting an ecological match. Macaque neurons seem better able to code contrasts that are slightly higher on average than those found in the natural environment.

The range of contrasts in natural scenes is generally thought to far exceed the limited dynamic ranges of individual contrast-encoding neurons in the primary visual cortex. The visual system may employ gain-control mechanisms (Ohzawa et al. 1985) to compensate for the mismatch between the range of natural contrast energies and the limited dynamic range of visual neurons; one proposed mechanism is contrast normalisation or non-specific suppression (Heeger 1992a). This paper aims to evaluate the role of contrast normalisation in human contrast perception, using a computer model of primary visual cortex. The model uses orthogonal pairs of Gabor patches to simulate simple-cell receptive-fields to calculate local, band-limited contrast in a series of 50 digitised photographs of natural scenes. The average range of contrast energies in each image was 2.29 log units, while the "lifetime range" each model simple cell would see across all images was 2.98 log units. These ranges are greater than the dynamic range of real mammalian simple cells. Contrast normalisation (dividing contrast responses by the summed responses of all nearby neurons) reduces contrast ranges, perhaps sufficiently to match them to neurons' limited dynamic ranges. Comparison of images taken under diffuse and direct lighting conditions showed that contrast normalisation can sometimes match these conditions effectively. This may lead to perceptual contrast constancy in the face of spurious changes in contrast caused by natural environmental conditions.

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Purpose To investigate the efficacy of spatial and temporal contrast sensitivity (CS) tests for detecting early glaucoma in the presence of cataract Methods Twenty‐seven early glaucoma patients (mean age 60 ±10.2 years) with early cataractous signs were selected together with twenty‐seven control subjects matched for age and cataract type. Cataracts were graded using the grading scheme of Casser et al (1997). Measurements of grating spatial and temporal CS at 20 HZ in central vision were performed in each group for spatial frequencies (SF) 0.5, 1.5 and 3 c/d with and without glare. Visual acuity, visual fields sensitivity measurements and structural tests using Heidelberg Retina Tomograph (HRT) were also performed. Results Overall reduction in both spatial and temporal CS at all SF was found for glaucoma patients compared with cataract patients with a significant mean difference of 0.2 log units (p < 0.01). This difference correlated well with measurements of visual fields or and HRT parameters. The effect of the glare on CS was significant (p < 0.01) and was similar for both groups. A significant correlation (p< 0.05) was found between the glare factor and the glaucomatous damage assessed by HRT. Conclusion Our results indicate that both spatial and temporal CS tests can distinguish glaucomatous vision loss from vision loss resulting from cataracts, the temporal test providing better separation at higher SF. The CS reduction due to the presence of glare increased with the glaucomatous damage, suggesting that there maybe an increase in intraocular straylight in glaucoma. References: 1.Casser L, Fingeret M, and Woodcome T. Atlas of Primary Eyecare Procedures, ed 2, 1997