Identification of cell-type specific visual circuits in the ventral lateral geniculate nucleus

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PROJECT SUMMARY Information about the visual world is captured by the retina and transmitted by retinal ganglion cells (RGCs) to a diverse array of retino-recipient regions of the mammalian brain, including those in thalamic, hypothalamic, and midbrain regions. There is an organizational logic to these long-range retinal projections where RGCs, of which there are more than three dozen morphologically and functionally distinct subtypes, project to distinct and sometimes mutually exclusive retinorecipient regions. Many of these retinorecipient nuclei are critical to the execution of specific visual behaviors. To understand how visual information is processed and transmitted from the retina to these brain regions requires a detailed characterization of the full cohort of cells in both regions and an investigation into the types of circuits they are assembled into. This requires us to catalogue a cellular “parts list” in both the retina and brain. For some parts of the subcortical visual system, such a catalogue exists. However, for some retino-recipient nuclei the cellular parts list is either poorly characterized or missing. One such region that remains poorly characterized is the ventral lateral geniculate nucleus (vLGN), the third largest retino-recipient region in rodents. Therefore, our goal is to apply state-of-the-art single cell resolution transcriptomic sequencing with trans-synaptic viral tracing to identify, in an unbiased fashion, all types of retino-recipient cells in the vLGN. Two such cell types have been identified in preliminary studies (Pvalb+ and Penk+ cells) and surprisingly, these cell types occupy distinct, adjacent sublamina of vLGN. These anatomical divisions suggest that subtype-specific laminar distribution of retino-recipient cells in this region may be important for receiving, processing, and transmitting light-derived signals in parallel channels through the brain. We will test this hypothesis by identifying the specific inputs and outputs of these two subtypes of vLGN neurons.