AUTHOR=Jouty Jonathan , Hilgen Gerrit , Sernagor Evelyne , Hennig Matthias H. 

TITLE=Non-parametric Physiological Classification of Retinal Ganglion Cells in the Mouse Retina

JOURNAL=Frontiers in Cellular Neuroscience

VOLUME=Volume 12 - 2018

YEAR=2018

URL=https://www.frontiersin.org/journals/cellular-neuroscience/articles/10.3389/fncel.2018.00481

DOI=10.3389/fncel.2018.00481

ISSN=1662-5102

ABSTRACT=Retinal ganglion cells, the sole output neurons of the retina, exhibit surprising diversity. A recent study reported over 30 distinct types in the mouse retina, indicating that the processing of visual information is highly parallelised in the brain. The advent of high density multi-electrode arrays now enables recording from many hundreds to thousands of neurons from a single retina. Here we describe a method for automatic classification of large-scale retinal recordings using a simple stimulus paradigm and a spike train distance measure as a clustering metric. We evaluate this approach with synthetic spike trains, and demonstrate that the major known cell types are discovered in a high-density recording from a mouse retina. We find that the major known cell types are identified from a single high-density recording session from the mouse retina with about 1000 retinal ganglion cells. As a parameter-free method, it is broadly applicable for the physiological classification of sensory neurons.