Slow feature analysis on retinal waves leads to V1 complex cells.

The developing visual system of many mammalian species is partially structured and organized even before the onset of vision. Spontaneous neural activity, which spreads in waves across the retina, has been suggested to play a major role in these prenatal structuring processes. Recently, it has been...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Sven Dähne, Niko Wilbert, Laurenz Wiskott
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/711c96cdb6974ce19ca56ab62a9db65e
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:711c96cdb6974ce19ca56ab62a9db65e
record_format	dspace
spelling	oai:doaj.org-article:711c96cdb6974ce19ca56ab62a9db65e2021-11-18T05:52:53ZSlow feature analysis on retinal waves leads to V1 complex cells.1553-734X1553-735810.1371/journal.pcbi.1003564https://doaj.org/article/711c96cdb6974ce19ca56ab62a9db65e2014-05-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24810948/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358The developing visual system of many mammalian species is partially structured and organized even before the onset of vision. Spontaneous neural activity, which spreads in waves across the retina, has been suggested to play a major role in these prenatal structuring processes. Recently, it has been shown that when employing an efficient coding strategy, such as sparse coding, these retinal activity patterns lead to basis functions that resemble optimal stimuli of simple cells in primary visual cortex (V1). Here we present the results of applying a coding strategy that optimizes for temporal slowness, namely Slow Feature Analysis (SFA), to a biologically plausible model of retinal waves. Previously, SFA has been successfully applied to model parts of the visual system, most notably in reproducing a rich set of complex-cell features by training SFA with quasi-natural image sequences. In the present work, we obtain SFA units that share a number of properties with cortical complex-cells by training on simulated retinal waves. The emergence of two distinct properties of the SFA units (phase invariance and orientation tuning) is thoroughly investigated via control experiments and mathematical analysis of the input-output functions found by SFA. The results support the idea that retinal waves share relevant temporal and spatial properties with natural visual input. Hence, retinal waves seem suitable training stimuli to learn invariances and thereby shape the developing early visual system such that it is best prepared for coding input from the natural world.Sven DähneNiko WilbertLaurenz WiskottPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 10, Iss 5, p e1003564 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Sven Dähne Niko Wilbert Laurenz Wiskott Slow feature analysis on retinal waves leads to V1 complex cells.
description	The developing visual system of many mammalian species is partially structured and organized even before the onset of vision. Spontaneous neural activity, which spreads in waves across the retina, has been suggested to play a major role in these prenatal structuring processes. Recently, it has been shown that when employing an efficient coding strategy, such as sparse coding, these retinal activity patterns lead to basis functions that resemble optimal stimuli of simple cells in primary visual cortex (V1). Here we present the results of applying a coding strategy that optimizes for temporal slowness, namely Slow Feature Analysis (SFA), to a biologically plausible model of retinal waves. Previously, SFA has been successfully applied to model parts of the visual system, most notably in reproducing a rich set of complex-cell features by training SFA with quasi-natural image sequences. In the present work, we obtain SFA units that share a number of properties with cortical complex-cells by training on simulated retinal waves. The emergence of two distinct properties of the SFA units (phase invariance and orientation tuning) is thoroughly investigated via control experiments and mathematical analysis of the input-output functions found by SFA. The results support the idea that retinal waves share relevant temporal and spatial properties with natural visual input. Hence, retinal waves seem suitable training stimuli to learn invariances and thereby shape the developing early visual system such that it is best prepared for coding input from the natural world.
format	article
author	Sven Dähne Niko Wilbert Laurenz Wiskott
author_facet	Sven Dähne Niko Wilbert Laurenz Wiskott
author_sort	Sven Dähne
title	Slow feature analysis on retinal waves leads to V1 complex cells.
title_short	Slow feature analysis on retinal waves leads to V1 complex cells.
title_full	Slow feature analysis on retinal waves leads to V1 complex cells.
title_fullStr	Slow feature analysis on retinal waves leads to V1 complex cells.
title_full_unstemmed	Slow feature analysis on retinal waves leads to V1 complex cells.
title_sort	slow feature analysis on retinal waves leads to v1 complex cells.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/711c96cdb6974ce19ca56ab62a9db65e
work_keys_str_mv	AT svendahne slowfeatureanalysisonretinalwavesleadstov1complexcells AT nikowilbert slowfeatureanalysisonretinalwavesleadstov1complexcells AT laurenzwiskott slowfeatureanalysisonretinalwavesleadstov1complexcells
_version_	1718424734465523712

Slow feature analysis on retinal waves leads to V1 complex cells.

Ejemplares similares