Feature Detection by Retinal Ganglion Cells

Annu Rev Vis Sci. 2022 Sep 15;8:135-169. doi: 10.1146/annurev-vision-100419-112009. Epub 2022 Apr 6.

Abstract

Retinal circuits transform the pixel representation of photoreceptors into the feature representations of ganglion cells, whose axons transmit these representations to the brain. Functional, morphological, and transcriptomic surveys have identified more than 40 retinal ganglion cell (RGC) types in mice. RGCs extract features of varying complexity; some simply signal local differences in brightness (i.e., luminance contrast), whereas others detect specific motion trajectories. To understand the retina, we need to know how retinal circuits give rise to the diverse RGC feature representations. A catalog of the RGC feature set, in turn, is fundamental to understanding visual processing in the brain. Anterograde tracing indicates that RGCs innervate more than 50 areas in the mouse brain. Current maps connecting RGC types to brain areas are rudimentary, as is our understanding of how retinal signals are transformed downstream to guide behavior. In this article, I review the feature selectivities of mouse RGCs, how they arise, and how they are utilized downstream. Not only is knowledge of the behavioral purpose of RGC signals critical for understanding the retinal contributions to vision; it can also guide us to the most relevant areas of visual feature space.

Keywords: direction selectivity; looming; luminance contrast; object motion; orientation selectivity; receptive field.

Publication types

  • Review

MeSH terms

  • Animals
  • Axons
  • Brain
  • Mice
  • Retina* / physiology
  • Retinal Ganglion Cells* / physiology
  • Vision, Ocular