Representing where along with what information in a model of a cortical patch.

Behaving in the real world requires flexibly combining and maintaining information about both continuous and discrete variables. In the visual domain, several lines of evidence show that neurons in some cortical networks can simultaneously represent information about the position and identity of obj...

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Autores principales:	Yasser Roudi, Alessandro Treves
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2008
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/3627db17e4f84271919f8f028ee217d7
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id	oai:doaj.org-article:3627db17e4f84271919f8f028ee217d7
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spelling	oai:doaj.org-article:3627db17e4f84271919f8f028ee217d72021-11-25T05:41:22ZRepresenting where along with what information in a model of a cortical patch.1553-734X1553-735810.1371/journal.pcbi.1000012https://doaj.org/article/3627db17e4f84271919f8f028ee217d72008-03-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/18369416/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Behaving in the real world requires flexibly combining and maintaining information about both continuous and discrete variables. In the visual domain, several lines of evidence show that neurons in some cortical networks can simultaneously represent information about the position and identity of objects, and maintain this combined representation when the object is no longer present. The underlying network mechanism for this combined representation is, however, unknown. In this paper, we approach this issue through a theoretical analysis of recurrent networks. We present a model of a cortical network that can retrieve information about the identity of objects from incomplete transient cues, while simultaneously representing their spatial position. Our results show that two factors are important in making this possible: A) a metric organisation of the recurrent connections, and B) a spatially localised change in the linear gain of neurons. Metric connectivity enables a localised retrieval of information about object identity, while gain modulation ensures localisation in the correct position. Importantly, we find that the amount of information that the network can retrieve and retain about identity is strongly affected by the amount of information it maintains about position. This balance can be controlled by global signals that change the neuronal gain. These results show that anatomical and physiological properties, which have long been known to characterise cortical networks, naturally endow them with the ability to maintain a conjunctive representation of the identity and location of objects.Yasser RoudiAlessandro TrevesPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 4, Iss 3, p e1000012 (2008)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Yasser Roudi Alessandro Treves Representing where along with what information in a model of a cortical patch.
description	Behaving in the real world requires flexibly combining and maintaining information about both continuous and discrete variables. In the visual domain, several lines of evidence show that neurons in some cortical networks can simultaneously represent information about the position and identity of objects, and maintain this combined representation when the object is no longer present. The underlying network mechanism for this combined representation is, however, unknown. In this paper, we approach this issue through a theoretical analysis of recurrent networks. We present a model of a cortical network that can retrieve information about the identity of objects from incomplete transient cues, while simultaneously representing their spatial position. Our results show that two factors are important in making this possible: A) a metric organisation of the recurrent connections, and B) a spatially localised change in the linear gain of neurons. Metric connectivity enables a localised retrieval of information about object identity, while gain modulation ensures localisation in the correct position. Importantly, we find that the amount of information that the network can retrieve and retain about identity is strongly affected by the amount of information it maintains about position. This balance can be controlled by global signals that change the neuronal gain. These results show that anatomical and physiological properties, which have long been known to characterise cortical networks, naturally endow them with the ability to maintain a conjunctive representation of the identity and location of objects.
format	article
author	Yasser Roudi Alessandro Treves
author_facet	Yasser Roudi Alessandro Treves
author_sort	Yasser Roudi
title	Representing where along with what information in a model of a cortical patch.
title_short	Representing where along with what information in a model of a cortical patch.
title_full	Representing where along with what information in a model of a cortical patch.
title_fullStr	Representing where along with what information in a model of a cortical patch.
title_full_unstemmed	Representing where along with what information in a model of a cortical patch.
title_sort	representing where along with what information in a model of a cortical patch.
publisher	Public Library of Science (PLoS)
publishDate	2008
url	https://doaj.org/article/3627db17e4f84271919f8f028ee217d7
work_keys_str_mv	AT yasserroudi representingwherealongwithwhatinformationinamodelofacorticalpatch AT alessandrotreves representingwherealongwithwhatinformationinamodelofacorticalpatch
_version_	1718414511132639232

Representing where along with what information in a model of a cortical patch.

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