Decomposition of retinal ganglion cell electrical images for cell type and functional inference.

ABSTRACT: Identifying neuronal cell types and their biophysical properties based on their extracellular electrical features is a major challenge for experimental neuroscience and the development of high-resolution brain-machine interfaces. One example is identification of retinal ganglion cell (RGC) types and their visual response properties, which is fundamental for developing future electronic implants that can restore vision. The electrical image (EI) of a RGC, or the mean spatio-temporal voltage footprint of its recorded spikes on a high-density electrode array, contains substantial information about its anatomical, morphological, and functional properties. However, the analysis of these properties is complex because of the high-dimensional nature of the EI. We present a novel optimization-based

SUBMITTER: Wu EG 

PROVIDER: S-EPMC10659265 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature