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Functional connectivity in the retina at the resolution of photoreceptors

To understand a neural circuit requires knowing its connectivity. This paper reports measurements of functional connectivity between the input and ouput layers of the retina at single cell resolution and its implications for color vision. Multi-electrode technology was employed to record simultaneou...

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Detalles Bibliográficos
Autores principales: Field, Greg D., Gauthier, Jeffrey L., Sher, Alexander, Greschner, Martin, Machado, Timothy, Jepson, Lauren H., Shlens, Jonathon, Gunning, Deborah E., Mathieson, Keith, Dabrowski, Wladyslaw, Paninski, Liam, Litke, Alan M., Chichilnisky, E.J.
Formato: Texto
Lenguaje:English
Publicado: 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2953734/
https://www.ncbi.nlm.nih.gov/pubmed/20930838
http://dx.doi.org/10.1038/nature09424
Descripción
Sumario:To understand a neural circuit requires knowing its connectivity. This paper reports measurements of functional connectivity between the input and ouput layers of the retina at single cell resolution and its implications for color vision. Multi-electrode technology was employed to record simultaneously from complete populations of the retinal ganglion cell types (midget, parasol, small bistratified) that transmit high-resolution visual signals to the brain. Fine-grained visual stimulation was used to identify the location, type and strength of the functional input of each cone photoreceptor to each ganglion cell. The populations of ON and OFF midget and parasol cells each sampled the complete population of long and middle wavelength sensitive cones. However, only OFF midget cells frequently received strong input from short wavelength sensitive cones. ON and OFF midget cells exhibited a small non-random tendency to selectively sample from either long or middle wavelength sensitive cones, to a degree not explained by clumping in the cone mosaic. These measurements reveal computations in a neural circuit at the elementary resolution of individual neurons.