Unexpected functional diversity among mouse retinal ganglion cell types


Purpose: Retinal circuits compute visual features in parallel and send this information to the brain through dedicated channels represented by the retinal ganglion cell (RGC) types. Anatomical studies have suggested up to 22 morphological RGC types, indicating that as many functional channels may form the output of the retina. Here we show that this estimate may need to be at least doubled to reflect the true functional diversity.Methods: To reliably record from every cell in the ganglion cell layer we used bulk-electroporation (Briggman & Euler, 2011) and two-photon Ca 2+ imaging. A standardized stimulus set, including temporal full-field stimulation, local motion, and dense noise for receptive field mapping, was presented to the retina. Some recordings were obtained from transgenic mice (PV, Pcp2), in which distinct RGC subsets are fluorescently labelled. Also, electrical single-cell recordings were performed to …

Matthias Bethge
Matthias Bethge
Professor for Computational Neuroscience and Machine Learning & Director of the Tübingen AI Center

Matthias Bethge is Professor for Computational Neuroscience and Machine Learning at the University of Tübingen and director of the Tübingen AI Center, a joint center between Tübingen University and MPI for Intelligent Systems that is part of the German AI strategy.