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Abstract

In the retina, the stream of incoming visual information is split into multiple parallel channels, formed by different kinds of photoreceptors (PRs), bipolar cells (BCs) and ganglion cells (RGCs). These cells form complex circuits with additional interneurons tuning the channels to distinct
sets of visual features. The RGCs relay the output of each channel to the brain—understanding how the visual scenery is encoded by the outputs of the approximately 20 RGC types will thus yield a complete picture of the representation of the visual scene available to the brain.
To identify a functional fingerprint for each RGC type in the mouse retina, we use 2P imaging to measure Ca++ activity in RGCs evoked by a set of stimuli, including frequency/contrast modulated full-field and white noise stimuli. So far our database contains recordings of over
10,000 cells from the RGC layer. In addition, we obtained recordings from transgenic PV1 mice, in which 8 morphologically distinct RGC types are fluorescently labeled and can be identified based on their anatomy. Moreover, we performed single-cell recordings from a few dozen RGCs to relate their spiking responses to the somatic calcium signals and to compare their morphologies with published RGC catalogues.
We implemented a probabilistic clustering framework for separating RGCs into functional types based on features extracted from their responses to the different visual stimuli using PCA. We used a semi-supervised mixture of Gaussians Clustering algorithm, which allowed us to
incorporate the uncertain label information provided by the recordings from the PV1 mice into the clustering. For our data, we obtain 25–29 functional clusters, which separate into 17–21 RGC clusters and 8 displaced amacrine cell (dAC) clusters, as verified using glutamatedecarboxylase (GAD) immunostaining. These numbers match well the number of RGC and dAC types expected in mouse retina. The RGC types include many known cell types (off and on alpha, W3, on-off direction-selective), as verified using our single cell data (e.g., alpha RGCs) and additional information available (e.g., soma size/shape and retinal tiling). In addition, they include new functional RGC types, such as a contrast-suppressed type, not readily matched to
previously described ones. Our results suggest that a functional fingerprint for each RGC in the mouse retina is within reach.