Frontiers in Neuroscience (Oct 2015)
A Method for Electrophysiological Characterization of Hamster Retinal Ganglion Cells Using a High-Density CMOS Microelectrode Array
Abstract
Knowledge of neuronal cell types in the mammalian retina is important for the understanding of human retinal disease and the advancement of sight-restoring technology, such as retinal prosthetic devices. A somewhat less utilized animal model for retinal research is the hamster, which has a visual system that is characterized by an area centralis and a wide visual field with a broad binocular component. The hamster retina is optimally suited for recording on the microelectrode array (MEA), because it intrinsically lies flat on the MEA surface and yields robust, large-amplitude signals. However, information in the literature about hamster retinal ganglion cell functional types is scarce. The goal of our work is to develop a method featuring a high-density (HD) Complementary metal-oxide-semiconductor (CMOS) MEA technology along with a sequence of standardized visual stimuli in order to categorize ganglion cells in isolated Syrian Hamster (Mesocricetus auratus) retina. Since the HD-MEA is capable of recording at a higher spatial resolution than most MEA systems (17.5 um electrode pitch), we capitalized on this feature and were able to record from a large proportion of RGCs within a selected region. Secondly, we chose our stimuli so that they could be run during the experiment without intervention or computation steps. The visual stimulus set was designed to activate the receptive fields of most ganglion cells in parallel and to incorporate various visual features to which different cell types respond uniquely. Based on the ganglion cell responses, basic cell properties were determined: direction selectivity, speed tuning, width tuning, transience and latency. These properties were clustered in order to identify ganglion cell types in the hamster retina. Ultimately, we recorded up to a cell density 2780 cells/mm2 at 2 mm (42°) from the optic nerve head. Using 5 parameters extracted from the responses to visual stimuli, we obtained 7 ganglion cell types.
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