A novel approach to the functional classification of retinal ganglion cells

Abstract

Retinal neurons are remarkedly diverse based on structure, function and genetic identity. Classifying these cells is a challenging task, requiring multimodal methodology. Here, we introduce a novel approach for retinal ganglion cell (RGC) classification, based on pharmacogenetics combined with immunohistochemistry and large-scale retinal electrophysiology. Our novel strategy allows grouping of cells sharing gene expression and understanding how these cell classes respond to basic and complex visual scenes. Our approach consists of several consecutive steps. First, the spike firing frequency is increased in RGCs co-expressing a certain gene ( Scnn1a or Grik4 ) using excitatory DREADDs (designer receptors exclusively activated by designer drugs) in order to single out activity originating specifically from these cells. Their spike location is then combined with post hoc immunostaining, to unequivocally characterize their anatomical and functional features. We grouped these isolated RGCs into multiple clusters based on spike train similarities. Using this novel approach, we were able to extend the pre-existing list of Grik4-expressing RGC types to a total of eight and, for the first time, we provide a phenotypical description of 13 Scnn1a-expressing RGCs. The insights and methods gained here can guide not only RGC classification but neuronal classification challenges in other brain regions as well.

Retinal self-organization: a model of retinal ganglion cells and starburst amacrine cells mosaic formation

“…The first hypothesis appears unlikely as RGCs are widely studied, especially with the emergence of large-scale and high-density MEA recordings [ 6 ], but also using morphological and molecular characterizations. Thus, it is unlikely that the existence of dense On RGC types (representing the majority of the On population, and so being the most common On type) has not been captured by at least one of these techniques.…”

“…One approach is to classify them into three functional and morphological groups depending on the sub-layer their dendrites laminate into in the inner plexiform layer, forming the On, Off and On-Off groups. In mouse, RGCs can however be divided into more than 40 types [3][4][5][6], each having different functional and anatomical characteristics. The number of RGCs sub-group varies between species, and for a different species, the density of these sub-groups is also known to greatly differ, varying from less than 50 cells mm −2 to more than 300 cells mm −2 [5].…”

Differences in nonlinearities determine retinal cell types

“…A key hypothesis in these more recent methods is that two neurons of the same type should extract the same feature, but in a different location of the visual space. For this reason, they should respond the same way if a stimulus that is spatially uniform is displayed [1], or if the stimulus is re-centered on the receptive field for each cell [3,5,9,11]. One of the most recent attempts to classify all ganglion cell types based on their function used, among other features, the responses to this spatially uniform "chirp" stimulus to divide cells in different types [1].…”