Monte Carlo methods for localization of cones given multielectrode retinal ganglion cell recordings.

Published

Journal Article

It has recently become possible to identify cone photoreceptors in primate retina from multi-electrode recordings of ganglion cell spiking driven by visual stimuli of sufficiently high spatial resolution. In this paper we present a statistical approach to the problem of identifying the number, locations, and color types of the cones observed in this type of experiment. We develop an adaptive Markov Chain Monte Carlo (MCMC) method that explores the space of cone configurations, using a Linear-Nonlinear-Poisson (LNP) encoding model of ganglion cell spiking output, while analytically integrating out the functional weights between cones and ganglion cells. This method provides information about our posterior certainty about the inferred cone properties, and additionally leads to improvements in both the speed and quality of the inferred cone maps, compared to earlier "greedy" computational approaches.

Full Text

Duke Authors

Cited Authors

  • Sadeghi, K; Gauthier, JL; Field, GD; Greschner, M; Agne, M; Chichilnisky, EJ; Paninski, L

Published Date

  • 2013

Published In

Volume / Issue

  • 24 / 1

Start / End Page

  • 27 - 51

PubMed ID

  • 23194406

Pubmed Central ID

  • 23194406

Electronic International Standard Serial Number (EISSN)

  • 1361-6536

Digital Object Identifier (DOI)

  • 10.3109/0954898X.2012.740140

Language

  • eng

Conference Location

  • England