Modeling a population of retinal ganglion cells with restricted Boltzmann machines

Abstract The retina is a complex circuit of the central nervous system whose aim is to encode visual stimuli prior the higher order processing performed in the visual cortex. Due to the importance of its role, modeling the retina to advance in interpreting its spiking activity output is a well studi...

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Autores principales:	Riccardo Volpi, Matteo Zanotto, Alessandro Maccione, Stefano Di Marco, Luca Berdondini, Diego Sona, Vittorio Murino
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/31a9c13128ea40bfa57355012cc8553e
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spelling	oai:doaj.org-article:31a9c13128ea40bfa57355012cc8553e2021-12-02T18:37:06ZModeling a population of retinal ganglion cells with restricted Boltzmann machines10.1038/s41598-020-73691-z2045-2322https://doaj.org/article/31a9c13128ea40bfa57355012cc8553e2020-10-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-73691-zhttps://doaj.org/toc/2045-2322Abstract The retina is a complex circuit of the central nervous system whose aim is to encode visual stimuli prior the higher order processing performed in the visual cortex. Due to the importance of its role, modeling the retina to advance in interpreting its spiking activity output is a well studied problem. In particular, it has been shown that latent variable models can be used to model the joint distribution of Retinal Ganglion Cells (RGCs). In this work, we validate the applicability of Restricted Boltzmann Machines to model the spiking activity responses of a large a population of RGCs recorded with high-resolution electrode arrays. In particular, we show that latent variables can encode modes in the RGC activity distribution that are closely related to the visual stimuli. In contrast to previous work, we further validate our findings by comparing results associated with recordings from retinas under normal and altered encoding conditions obtained by pharmacological manipulation. In these conditions, we observe that the model reflects well-known physiological behaviors of the retina. Finally, we show that we can also discover temporal patterns, associated with distinct dynamics of the stimuli.Riccardo VolpiMatteo ZanottoAlessandro MaccioneStefano Di MarcoLuca BerdondiniDiego SonaVittorio MurinoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-10 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Riccardo Volpi Matteo Zanotto Alessandro Maccione Stefano Di Marco Luca Berdondini Diego Sona Vittorio Murino Modeling a population of retinal ganglion cells with restricted Boltzmann machines
description	Abstract The retina is a complex circuit of the central nervous system whose aim is to encode visual stimuli prior the higher order processing performed in the visual cortex. Due to the importance of its role, modeling the retina to advance in interpreting its spiking activity output is a well studied problem. In particular, it has been shown that latent variable models can be used to model the joint distribution of Retinal Ganglion Cells (RGCs). In this work, we validate the applicability of Restricted Boltzmann Machines to model the spiking activity responses of a large a population of RGCs recorded with high-resolution electrode arrays. In particular, we show that latent variables can encode modes in the RGC activity distribution that are closely related to the visual stimuli. In contrast to previous work, we further validate our findings by comparing results associated with recordings from retinas under normal and altered encoding conditions obtained by pharmacological manipulation. In these conditions, we observe that the model reflects well-known physiological behaviors of the retina. Finally, we show that we can also discover temporal patterns, associated with distinct dynamics of the stimuli.
format	article
author	Riccardo Volpi Matteo Zanotto Alessandro Maccione Stefano Di Marco Luca Berdondini Diego Sona Vittorio Murino
author_facet	Riccardo Volpi Matteo Zanotto Alessandro Maccione Stefano Di Marco Luca Berdondini Diego Sona Vittorio Murino
author_sort	Riccardo Volpi
title	Modeling a population of retinal ganglion cells with restricted Boltzmann machines
title_short	Modeling a population of retinal ganglion cells with restricted Boltzmann machines
title_full	Modeling a population of retinal ganglion cells with restricted Boltzmann machines
title_fullStr	Modeling a population of retinal ganglion cells with restricted Boltzmann machines
title_full_unstemmed	Modeling a population of retinal ganglion cells with restricted Boltzmann machines
title_sort	modeling a population of retinal ganglion cells with restricted boltzmann machines
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/31a9c13128ea40bfa57355012cc8553e
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_version_	1718377789293330432

Modeling a population of retinal ganglion cells with restricted Boltzmann machines

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