Distributed fading memory for stimulus properties in the primary visual cortex.

It is currently not known how distributed neuronal responses in early visual areas carry stimulus-related information. We made multielectrode recordings from cat primary visual cortex and applied methods from machine learning in order to analyze the temporal evolution of stimulus-related information...

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Autores principales:	Danko Nikolić, Stefan Häusler, Wolf Singer, Wolfgang Maass
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2009
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/5ac22393c64e454db0c364273557ffbc
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spelling	oai:doaj.org-article:5ac22393c64e454db0c364273557ffbc2021-11-25T05:34:27ZDistributed fading memory for stimulus properties in the primary visual cortex.1544-91731545-788510.1371/journal.pbio.1000260https://doaj.org/article/5ac22393c64e454db0c364273557ffbc2009-12-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20027205/?tool=EBIhttps://doaj.org/toc/1544-9173https://doaj.org/toc/1545-7885It is currently not known how distributed neuronal responses in early visual areas carry stimulus-related information. We made multielectrode recordings from cat primary visual cortex and applied methods from machine learning in order to analyze the temporal evolution of stimulus-related information in the spiking activity of large ensembles of around 100 neurons. We used sequences of up to three different visual stimuli (letters of the alphabet) presented for 100 ms and with intervals of 100 ms or larger. Most of the information about visual stimuli extractable by sophisticated methods of machine learning, i.e., support vector machines with nonlinear kernel functions, was also extractable by simple linear classification such as can be achieved by individual neurons. New stimuli did not erase information about previous stimuli. The responses to the most recent stimulus contained about equal amounts of information about both this and the preceding stimulus. This information was encoded both in the discharge rates (response amplitudes) of the ensemble of neurons and, when using short time constants for integration (e.g., 20 ms), in the precise timing of individual spikes (<or= approximately 20 ms), and persisted for several 100 ms beyond the offset of stimuli. The results indicate that the network from which we recorded is endowed with fading memory and is capable of performing online computations utilizing information about temporally sequential stimuli. This result challenges models assuming frame-by-frame analyses of sequential inputs.Danko NikolićStefan HäuslerWolf SingerWolfgang MaassPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Biology, Vol 7, Iss 12, p e1000260 (2009)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Danko Nikolić Stefan Häusler Wolf Singer Wolfgang Maass Distributed fading memory for stimulus properties in the primary visual cortex.
description	It is currently not known how distributed neuronal responses in early visual areas carry stimulus-related information. We made multielectrode recordings from cat primary visual cortex and applied methods from machine learning in order to analyze the temporal evolution of stimulus-related information in the spiking activity of large ensembles of around 100 neurons. We used sequences of up to three different visual stimuli (letters of the alphabet) presented for 100 ms and with intervals of 100 ms or larger. Most of the information about visual stimuli extractable by sophisticated methods of machine learning, i.e., support vector machines with nonlinear kernel functions, was also extractable by simple linear classification such as can be achieved by individual neurons. New stimuli did not erase information about previous stimuli. The responses to the most recent stimulus contained about equal amounts of information about both this and the preceding stimulus. This information was encoded both in the discharge rates (response amplitudes) of the ensemble of neurons and, when using short time constants for integration (e.g., 20 ms), in the precise timing of individual spikes (<or= approximately 20 ms), and persisted for several 100 ms beyond the offset of stimuli. The results indicate that the network from which we recorded is endowed with fading memory and is capable of performing online computations utilizing information about temporally sequential stimuli. This result challenges models assuming frame-by-frame analyses of sequential inputs.
format	article
author	Danko Nikolić Stefan Häusler Wolf Singer Wolfgang Maass
author_facet	Danko Nikolić Stefan Häusler Wolf Singer Wolfgang Maass
author_sort	Danko Nikolić
title	Distributed fading memory for stimulus properties in the primary visual cortex.
title_short	Distributed fading memory for stimulus properties in the primary visual cortex.
title_full	Distributed fading memory for stimulus properties in the primary visual cortex.
title_fullStr	Distributed fading memory for stimulus properties in the primary visual cortex.
title_full_unstemmed	Distributed fading memory for stimulus properties in the primary visual cortex.
title_sort	distributed fading memory for stimulus properties in the primary visual cortex.
publisher	Public Library of Science (PLoS)
publishDate	2009
url	https://doaj.org/article/5ac22393c64e454db0c364273557ffbc
work_keys_str_mv	AT dankonikolic distributedfadingmemoryforstimuluspropertiesintheprimaryvisualcortex AT stefanhausler distributedfadingmemoryforstimuluspropertiesintheprimaryvisualcortex AT wolfsinger distributedfadingmemoryforstimuluspropertiesintheprimaryvisualcortex AT wolfgangmaass distributedfadingmemoryforstimuluspropertiesintheprimaryvisualcortex
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Distributed fading memory for stimulus properties in the primary visual cortex.

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