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...

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Autores principales: Sven Dähne, Niko Wilbert, Laurenz Wiskott
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Lenguaje:EN
Publicado: Public Library of Science (PLoS) 2014
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Acceso en línea:https://doaj.org/article/711c96cdb6974ce19ca56ab62a9db65e
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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
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