Efficient coding of spatial information in the primate retina.
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2012-11
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Sensory neurons have been hypothesized to efficiently encode signals from the natural environment subject to resource constraints. The predictions of this efficient coding hypothesis regarding the spatial filtering properties of the visual system have been found consistent with human perception, but they have not been compared directly with neural responses. Here, we analyze the information that retinal ganglion cells transmit to the brain about the spatial information in natural images subject to three resource constraints: the number of retinal ganglion cells, their total response variances, and their total synaptic strengths. We derive a model that optimizes the transmitted information and compare it directly with measurements of complete functional connectivity between cone photoreceptors and the four major types of ganglion cells in the primate retina, obtained at single-cell resolution. We find that the ganglion cell population exhibited 80% efficiency in transmitting spatial information relative to the model. Both the retina and the model exhibited high redundancy (~30%) among ganglion cells of the same cell type. A novel and unique prediction of efficient coding, the relationships between projection patterns of individual cones to all ganglion cells, was consistent with the observed projection patterns in the retina. These results indicate a high level of efficiency with near-optimal redundancy in visual signaling by the retina.
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Doi, Eizaburo, Jeffrey L Gauthier, Greg D Field, Jonathon Shlens, Alexander Sher, Martin Greschner, Timothy A Machado, Lauren H Jepson, et al. (2012). Efficient coding of spatial information in the primate retina. The Journal of neuroscience : the official journal of the Society for Neuroscience, 32(46). pp. 16256–16264. 10.1523/JNEUROSCI.4036-12.2012 Retrieved from https://hdl.handle.net/10161/17863.
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Greg D. Field
My laboratory studies how the retina processes visual scenes and transmits this information to the brain. We use multi-electrode arrays to record the activity of hundreds of retina neurons simultaneously in conjunction with transgenic mouse lines and chemogenetics to manipulate neural circuit function. We are interested in three major areas. First, we work to understand how neurons in the retina are functionally connected. Second we are studying how light-adaptation and circadian rhythms alter visual processing in the retina. Finally, we are working to understand the mechanisms of retinal degenerative conditions and we are investigating potential treatments in animal models.
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