Literature DB >> 21273316

Physiological clustering of visual channels in the mouse retina.

Karl Farrow1, Richard H Masland.   

Abstract

Anatomy predicts that mammalian retinas should have in excess of 12 physiological channels, each encoding a specific aspect of the visual scene. Although several channels have been correlated with morphological cell types, the number of morphological types generally exceeds the known physiological types. Here, we attempted to sort the ganglion cells of the mouse retina purely on a physiological basis. The null hypothesis was that the outputs of the ganglion cells form a continuum or should be divided into only a few types. We recorded the spiking output of 471 retinal ganglion cells on a multielectrode array while presenting 4 classes of visual stimuli. Five parameters were chosen to describe each cell's response characteristics, including relative amplitude of the ON and OFF responses, response latency, response transience, direction selectivity, and the receptive field surround. We compared the results of four clustering routines and judged the results using the relevant validation indices. The optimal partition was the 12-cluster solution of the Fuzzy Gustafson-Kessel algorithm. This classification contained three visual channels that carried predominately OFF responses, six that carried ON responses, and three that carried both ON and OFF information. They differed in other parameters as well. Other evidence suggests that the true number of cell types in the mouse retina may be somewhat larger than 12, and a definitive typology will probably require broader stimulus sets and characterization of more response parameters. Nonetheless, the present results do allow us to reject the null hypothesis: it appears that in addition to well-known cell types (such as the ON-OFF direction selectivity cells) numerous other cell classes can be identified in the mouse retina based solely on their responses to a standard set of simple visual stimuli.

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Year:  2011        PMID: 21273316      PMCID: PMC3075295          DOI: 10.1152/jn.00331.2010

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


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