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.
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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