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Abstract:
Right at the first synapse in the mammalian retina, the stream of incoming visual information is split into multiple parallel information channels, preprocessed in the retinal network and relayed to the brain via different types of retinal ganglion cells (RGCs). About 20 different morphological RGC types have been described, with each RGC population tiling the retinal surface with its dendritic arbors. Here, we simultaneously record from all RGC types at one retinal location to obtain a complete sample of the information sent to the brain and to understand how the representation of spatio-temporal information in a local image patch is distributed across different RGC types. Here show that retinal ganglion cells can be clustered into functionally defined classes based on their Ca2+-responses to simple light stimuli.
We recorded light-evoked Ca2+ activity at single-cell resolution from groups of more than 500 neighboring RGCs loaded with synthetic Ca2+ indicator dyes in whole-mounted mouse retina using two-photon (2P) microscopy. We used a simple full-field light stimulus composed of luminance changes and a temporal frequency chirp. Over 80% of the cells responded reliably to the full field stimulus. Single cell activity patterns could be clustered into more than 15 functionally distinct types using a simple k-means algorithm, yielding about 40% ON cells, 25% ON/OFF and 15% OFF cells, in agreement with previous reports.
In addition, presentation of spatially modulated stimuli such as moving bars and checker-boards allowed us to quickly and reliably identify different previously described functional types such as direction selective GCs. We will further verify the functional clustering by morphological identification or patch-clamp recordings. This is possible because the imaged RGCs remain accessible to microelectrodes and, thus, can be dye-filled for morphological identification or targeted for patch-clamp recordings, in contrast to multi-electrode recordings.
We now aim to refine our battery of simple stimuli to be able to functionally cluster all >20 morphologically described RGCs in the mouse retina. Our approach allows us to create an inventory of all retinal ganglion cells present at a single retinal location. This local retinal “information fingerprint” should be very informative, not only for our understanding of neuronal computations in the healthy retina, but also as a research tool for evaluating specific functional deficiencies in diseased or degenerating retinae.
