Lesions of the optic tract produce a distinctive pattern of optic atrophy and visual field loss and may be due to either congenital or acquired causes. We report a case of a congenital optic tract syndrome and correlate the magnetic resonance imaging findings with the appearance of nerve fiber layer defects found by confocal scanning laser ophthalmoscopy.

Purpose: The purpose of the study is to identify the anatomic abnormalities associated with an absolute scotoma and the location and stability of fixation in patients with subfoveal neovascularization in age-related macular degeneration, presumed ocular histoplasmosis syndrome, and other disorders.Methods: Scanning laser ophthalmoscope microperimetry was superimposed on color fundus photographs and fluorescein angiograms of 21 eyes with subfoveal neovascular membranes secondary to age-related macular degeneration (14 eyes) and presumed ocular histoplasmosis syndrome (7 eyes). The authors determined the location and the area occupied by the absolute scotoma and each of the following subretinal lesions: subretinal hemorrhage, neurosensory retinal detachment, retinal pigment epithelial (RPE) atrophy, RPE hyperplasia, atrophy of the choriocapillaris, hard exudates, and the subfoveal neovascular membrane. The area of absolute scotoma determined by scanning laser ophthalmoscope microperimetry was superimposed on the anatomic lesions. The authors calculated the relative risk ratio (RR) of an absolute scotoma occurring in regions corresponding to each anatomic abnormality, and determined the preferred location and stability of fixation in each eye.Results: An absolute scotoma was present in areas of chorioretinal scar (RR = 107.61), RPE atrophy (RR = 9.97), subretinal hemorrhage (RR = 2.88), and the neovascular membrane (RR = 1.86). Fixation was stable in all patients with presumed ocular histoplasmosis syndrome but only 29% of patients with age-related macular degeneration. Fifty-five percent of patients with stable fixation fixated over an area of RPE hyperplasia. Conclusion: The relative risk of an absolute scotoma is highest over areas of chorioretinal scars, RPE atrophy, subretinal hemorrhage, and the neovascular membrane. Fixation is more stable in patients with subfoveal neovascularization from presumed ocular histoplasmosis syndrome than with age-related macular degeneration and frequently is present over an area of RPE hyperplasia.

A number of autosomal recessive syndromes feature both sensorineural hearing loss and retinal degeneration. The mouse mutant tubby also combines hearing loss with progressive retinal degeneration, and thus may constitute a useful model of one form of human sensorineural deafness/retinal dystrophic syndrome. It has not been directly demonstrated that the hearing loss in this mouse involves the cochlea, however. We have examined the cochleas of adult tubby mice using light microscopy. The tubby cochlea shows pronounced degeneration of the organ of Corti and loss of afferent neurons in the base, with relative sparing of the apex. Our findings support the tubby mouse as a model of human sensorineural deafness/retinal dystrophic syndrome. Possible human counterparts include Usher's, Alstrom's, and Bardet-Biedl syndromes.

The nerve fiber layer (NFL), consisting of the axons of ganglion cells sweeping across the inner surface of the retina to the disc, transmits all the visual information from the eye to the brain. The normal, topographically regular pattern of nerve fibers is illustrated in Figure 1. Ophthalmoscopically, the nerve fiber layer is recognized as a pattern of subtle striations emanating from the disc a short distance; the striations are evidently bundles of axons contained within glial tunnels formed by Muller's cell processes6. Glaucoma and other optic neuropathies damage the nerve fibers and cause defects within the pattern. The bundles are fairly easy to see near the disc, and the circumpapillary nerve fibers have proved useful to image, because fiber damage and defects in the striation pattern sometimes precede detectable visual field defects. It has previously proved impossible, however, to image non-invasively the details of the perifoveally originating papillomacular bundles. Because the visual information from the perifoveal area is crucial to visual performance and because some neuropathies affect central vision preferentially (e.g., Leber's optic neuropathy), it may be useful to visualize the papillomacular bundle near the fovea, where a focal pattern of loss might be noticeable and well-correlated to focal visual deficits.

It is well established that cortical neurons frequently show different preferred drift directions for random dots and gratings. Dot stimuli often produce two preferred directions which are arranged symmetrically on either side of the preferred directions for gratings. Based on their filter properties in three-dimensional (3-D) Fourier space and on the 3-D power spectra of drifting dot patterns, we estimated the optimal direction to drifting dots for ten neurons in the striate cortex of five adult cats. These estimates frequently gave two optimal directions, one on either side of the optimal direction to gratings. The angle between the two estimated peaks increases with drift speed. Predicted and actual angles were in reasonably good agreement. We conclude, therefore, that the directional selectivity of cortical neurons to drifting random dot patterns can be understood from linear filtering properties. For this reason, the directional tuning to drifting dot patterns seems to reflect the same mechanisms that mediate the responses to sinusoidal gratings and do not require a separate directional mechanism.

We describe here a new view of primary visual cortex (V1) based on measurements of neural responses in V1 to patterns called 'illusory contours' (Fig. 1a, b). Detection of an object's boundary contours is a fundamental visual task. Boundary contours are defined by discontinuities not only in luminance and colour, but also in texture, disparity and motion. Two theoretical approaches can account for illusory contour perception. The cognitive approach emphasizes top-down processes. An alternative emphasizes bottom-up processing. This latter view is supported by (1) stimulus constraints for illusory contour perception and (2) the discovery by von der Heydt and Peterhans of neurons in extrastriate visual area V2 (but not in V1) of macaque monkeys that respond to illusory contours. Using stimuli different from those used previously, we found illusory contour responses in about half the neurons studied in V1 of macaque monkeys. Therefore, there are neurons as early as V1 with the computational power to detect illusory contours and to help distinguish figure from ground.

We measured the spatial-frequency tuning of cells at regular intervals along tangential probes through the monkey striate cortex and correlated the recording sites with the cortical cytochrome oxidase (CytOx) patterns to address three questions with regard to the cortical spatial-frequency organization. (i) Is there a periodic anatomical arrangement of cells tuned to different spatial-frequency ranges? We found there is, because the spatial-frequency tuning of cells along tangential probes changed systematically, varying from a low frequency to a middle range to high frequencies and back again repeatedly over distances of about 0.6-0.7 mm. (ii) Are there just two populations of cells, low-frequency and high-frequency units, at a given eccentricity (perhaps corresponding to the magno- and parvocellular geniculate pathways) or is there a continuum of spatial-frequency peaks? We found a continuum of peak tuning. Most cells are tuned to intermediate spatial frequencies and form a unimodal rather than a bimodal distribution of cell peaks. Furthermore, the cells with different peak frequencies were found to be continuously and smoothly distributed across a module. (iii) What is the relation between the physiological spatial-frequency organization and the regions of high CytOx concentration ("blobs")? We found a systematic correlation between the topographical variation in spatial-frequency tuning and the modular CytOx pattern, which also varied continuously in density. Low-frequency cells are at the center of the blobs, and cells tuned to increasingly higher spatial frequencies are at increasing radial distances.

1. There are several reports that random dot patterns are potent stimuli for cortical complex cells but not for simple cells. This finding is regarded as evidence against Hubel and Wiesel's hierarchical model of cortical circuitry, in which simple cells are the principal input to complex cells. We have reinvestigated the question quantitatively by recording responses to dot patterns from 106 cells in area 17 and the 17/18 border region of normal adult cats. 2. The cells were classified as simple (n = 62) or complex (n = 40) (4 were end stopped or hypercomplex) on the basis of whether they gave modulated (AC) or unmodulated (DC) responses to drifting sine gratings. 3. Although there are large within-group differences, we found both simple and complex cells that respond to bright random dots on a dark background, drifted across the receptive field at 3 degrees/s. The responses at the optimal direction averaged 6.2 and 18.1 spikes/s (spontaneous activity subtracted) for simple and complex cells, respectively. 4. We also recorded responses to drifting sine gratings. Complex cells were also found to respond more than simple cells to these stimuli. For each cell, we calculated a dot index expressing the dot response relative to grating response. The dot index averaged 0.43 for simple cells and 0.55 for complex cells. It therefore appears that much of the difference in response to dot patterns reflects a difference in general responsivity. 5. In subsamples of cells, we examined the effects of varying dot density, dot size, and drift velocity. These variables affect different cells in a manner largely independent of cell class. Most simple cells in our sample responded well to random dot patterns at several velocities, at two different dot sizes and at both 3 and 50% dot densities. 6. Our results agree with previous studies in showing that complex cells respond more vigorously than simple cells to dot patterns, but the fact that many simple cells also respond to these stimuli makes our results consistent with a hierarchical model of cortical circuitry.