Purpose: To study the variation of cone photoreceptor packing density across the retina in healthy subjects of different ages.
Methods: High-resolution adaptive optics scanning laser ophthalmoscope (AOSLO) systems were used to systematically image the retinas of two groups of subjects of different ages. Ten younger subjects (age range, 22-35 years) and 10 older subjects (age range, 50-65 years) were tested. Strips of cone photoreceptors, approximately 12° × 1.8° long were imaged for each of the four primary retinal meridians: superior, inferior, nasal, and temporal. Cone photoreceptors within the strips were counted, and cone photoreceptor packing density was calculated. Statistical analysis (three-way ANOVA) was used to calculate the interaction for cone photoreceptor packing density between age, meridian, and eccentricity.
Results: As expected, cone photoreceptor packing density was higher close to the fovea and decreased with increasing retinal eccentricity from 0.18 to 3.5 mm (∼0.6-12°). Older subjects had approximately 75% of the cone density at 0.18 mm (∼0.6°), and this difference decreased rapidly with eccentricity, with the two groups having similar cone photoreceptor packing densities beyond 0.5 mm retinal eccentricity on average.
Conclusions: Cone packing density in the living human retina decreases as a function of age within the foveal center with the largest difference being found at our most central measurement site. At all ages, the retina showed meridional difference in cone densities, with cone photoreceptor packing density decreasing faster with increasing eccentricity in the vertical dimensions than in the horizontal dimensions.
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http://dx.doi.org/10.1167/iovs.11-7199 | DOI Listing |
Previously we reported color matches measured in young adults using a newly developed multi-wavelength LED-based visual trichromator with which we estimated their individual L-, M- and S-cone spectral sensitivities. Here, we extend those measurements to include 70 additional observers aged between 8 to 80 years. As in our previous work, a series of color matching measurements were made to a reference white.
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Biology and Biochemistry PhD Programs, Graduate Center, City University of New York, New York, New York, United States.
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Institute of AI for Industries, Chinese Academy of Sciences Nanjing, 168, Tianquan Road, Nanjing 211135, China.
In this study, we designed a biomimetic artificial visual system (AVS) inspired by biological visual system that can process RGB images. Our approach begins by mimicking the photoreceptor cone cells to simulate the initial input processing followed by a learnable dendritic neuron model to replicate ganglion cells that integrate outputs from bipolar and horizontal cell simulations. To handle multi-channel integration, we utilize a nonlearnable dendritic neuron model to simulate the lateral geniculate nucleus (LGN), which consolidates outputs across color channels, an essential function in biological multi-channel processing.
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