Congenital optic tract syndrome: magnetic resonance imaging and scanning laser ophthalmoscopy findings.

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.

Correlation between scanning laser ophthalmoscope microperimetry and anatomic abnormalities in patients with subfoveal neovascularization.

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.

Temporal-frequency selectivity in monkey visual cortex.

We investigated the dynamics of neurons in the striate cortex (V1) and the lateral geniculate nucleus (LGN) to study the transformation in temporal-frequency tuning between the LGN and V1. Furthermore, we compared the temporal-frequency tuning of simple with that of complex cells and direction-selective cells with nondirection-selective cells, in order to determine whether there are significant differences in temporal-frequency tuning among distinct functional classes of cells within V1. In addition, we compared the cells in the primary input layers of V1 (4a, 4c alpha, and 4c beta) with cells in the layers that are predominantly second and higher order (2, 3, 4b, 5, and 6). We measured temporal-frequency responses to drifting sinusoidal gratings. For LGN neurons and simple cells, we used the amplitude and phase of the fundamental response. For complex cells, the elevation of impulse rate (F0) to a drifting grating was the response measure. There is significant low-pass filtering between the LGN and the input layers of V1 accompanied by a small, 3-ms increase in visual delay. There is further low-pass filtering between V1 input layers and the second- and higher-order neurons in V1. This results in an average decrease in high cutoff temporal-frequency between the LGN and V1 output layers of about 20 Hz and an increase in average visual latency of about 12-14 ms. One of the most salient results is the increased diversity of the dynamic properties seen in V1 when compared to the cells of the lateral geniculate, possibly reflecting specialization of function among cells in V1. Simple and complex cells had distributions of temporal-frequency tuning properties that were similar to each other. Direction-selective and nondirection-selective cells had similar preferred and high cutoff temporal frequencies, but direction-selective cells were almost exclusively band-pass while nondirection-selective cells distributed equally between band-pass and low-pass categories. Integration time, a measure of visual delay, was about 10 ms longer for V1 than LGN. In V1 there was a relatively broad distribution of integration times from 40-80 ms for simple cells and 60-100 ms for complex cells while in the LGN the distribution was narrower.

Cochlear and retinal degeneration in the tubby mouse.

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.

On the directional selectivity of cells in the visual cortex to drifting dot patterns.

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.

Macaque V1 neurons can signal 'illusory' contours.

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.

Properties of the recombination of one-dimensional motion signals into a pattern motion signal.

We have examined the human ability to determine the direction of movement of a variety of plaid patterns. The plaids were composed of two orthogonal sine-wave gratings. When the plaid components are of unequal spatial frequency or sometimes of unequal contrast, observers judge the direction of movement incorrectly. In terms of the two-stage model of Adelson and Movshon (1982), these errors may result from either a misjudgment in the perceived speeds of each of the components or a failure in the combination of one-dimensional component movements into a coherent direction of motion of the two-dimensional plaid pattern, or both. A comparison of the perceived direction of motion of plaids with the relative perceived speeds of the plaid component gratings suggest that both failures occur, but in different circumstances. The relative perceived speed of the plaid components was measured with a spatial and a temporal forced-choice technique, the former leading to larger differences. Our results support the notion that the visual system decomposes a moving plaid into oriented components and subsequently recombines the component motions.

Higher-order factors influencing the perception of sliding and coherence of a plaid.

The effect of several new stimulus parameters on the perception of a moving plaid pattern (the sum of two sine-wave gratings) were tested. It was found that: (i) the degree of perceived sliding is strongly influenced by the aperture configuration through which the plaid is viewed; (ii) the chromaticity of the sinusoidal components affects coherence in that more sliding is observed when the plaid components differ in hue, and there is less sliding when they are of the same hue; (iii) equiluminant plaids made of components equal in color almost never show any sliding; and (iv) sliding increases with viewing time. The coherence-sliding percept must therefore be influenced by color, by global interactions, and by adaptation or learning effects, thus suggesting a higher-level influence. These results are most easily modelled by separating the decision to carry out recombination from the process of recombination.

Classifying simple and complex cells on the basis of response modulation.

Hubel and Wiesel (1962; Journal of Physiology, London, 160, 106-154) introduced the classification of cortical neurons as simple and complex on the basis of four tests of their receptive field structure. These tests are partly subjective and no one of them unequivocally places neurons into distinct classes. A simple, objective classification criterion based on the form of the response to drifting sinusoidal gratings has been used by several laboratories, although it has been criticized by others. We review published and unpublished evidence which indicates that this simple and objective criterion reliability divides neurons of the striate cortex in both cats and monkeys into two groups that correspond closely to the classically-described simple and complex classes.

Spatial-frequency organization in primate striate cortex.

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.

Responses of simple and complex cells to random dot patterns: a quantitative comparison.

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.