Three small-receptive-field ganglion cells in the mouse retina are distinctly tuned to size, speed, and object motion

Jason Jacoby, Gregory W. Schwartz*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

59 Scopus citations


Retinal ganglion cells (RGCs) are frequently divided into functional types by their ability to extract and relay specific features from a visual scene, such as the capacity to discern local or global motion, direction of motion, stimulus orientation, contrast or uniformity, or the presence of large or small objects. Here we introduce three previously uncharacterized, nondirection-selective ON–OFF RGC types that represent a distinct set of feature detectors in the mouse retina. The three high-definition (HD) RGCs possess small receptive-field centers and strong surround suppression. They respond selectively to objects of specific sizes, speeds, and types of motion. We present comprehensive morphological characterization of theHDRGCs and physiological recordings of their light responses, receptive-field size and structure, and synaptic mechanisms of surround suppression. We also explore the similarities and differences between the HD RGCs and a well characterized RGC with a comparably small receptive field, the local edge detector, in response to moving objects and textures. We model populations of each RGC type to study how they differ in their performance tracking a moving object. These results, besides introducing three new RGC types that together constitute a substantial fraction of mouse RGCs, provide insights into the role of different circuits in shaping RGC receptive fields and establish a foundation for continued study of the mechanisms of surround suppression and the neural basis of motion detection.

Original languageEnglish (US)
Pages (from-to)610-625
Number of pages16
JournalJournal of Neuroscience
Issue number3
StatePublished - Jan 18 2017


  • Feature selectivity
  • Object motion
  • Retina
  • Retinal ganglion cell

ASJC Scopus subject areas

  • General Neuroscience


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