Unified classification of mouse retinal ganglion cells using function, morphology, and gene expression.

ABSTRACT: Classification and characterization of neuronal types are critical for understanding their function and dysfunction. Neuronal classification schemes typically rely on measurements of electrophysiological, morphological, and molecular features, but aligning such datasets has been challenging. Here, we present a unified classification of mouse retinal ganglion cells (RGCs), the sole retinal output neurons. We use visually evoked responses to classify 1,859 mouse RGCs into 42 types. We also obtain morphological or transcriptomic data from subsets and use these measurements to align the functional classification to publicly available morphological and transcriptomic datasets. We create an online database that allows users to browse or download the data and to classify RGCs from their light res

SUBMITTER: Goetz J 

PROVIDER: S-EPMC9364428 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature