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Can Attractor Network Models Account for the Statistics of Firing During Persistent Activity in Prefrontal Cortex?

Persistent activity observed in neurophysiological experiments in monkeys is thought to be the neuronal correlate of working memory. Over the last decade, network modellers have strived to reproduce the main features of these experiments. In particular, attractor network models have been proposed in...

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Detalles Bibliográficos
Autores principales: Barbieri, Francesca, Brunel, Nicolas
Formato: Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2570072/
https://www.ncbi.nlm.nih.gov/pubmed/18982114
http://dx.doi.org/10.3389/neuro.01.003.2008
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author Barbieri, Francesca
Brunel, Nicolas
author_facet Barbieri, Francesca
Brunel, Nicolas
author_sort Barbieri, Francesca
collection PubMed
description Persistent activity observed in neurophysiological experiments in monkeys is thought to be the neuronal correlate of working memory. Over the last decade, network modellers have strived to reproduce the main features of these experiments. In particular, attractor network models have been proposed in which there is a coexistence between a non-selective attractor state with low background activity with selective attractor states in which sub-groups of neurons fire at rates which are higher (but not much higher) than background rates. A recent detailed statistical analysis of the data seems however to challenge such attractor models: the data indicates that firing during persistent activity is highly irregular (with an average CV larger than 1), while models predict a more regular firing process (CV smaller than 1). We discuss here recent proposals that allow to reproduce this feature of the experiments.
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spelling pubmed-25700722008-11-03 Can Attractor Network Models Account for the Statistics of Firing During Persistent Activity in Prefrontal Cortex? Barbieri, Francesca Brunel, Nicolas Front Neurosci Neuroscience Persistent activity observed in neurophysiological experiments in monkeys is thought to be the neuronal correlate of working memory. Over the last decade, network modellers have strived to reproduce the main features of these experiments. In particular, attractor network models have been proposed in which there is a coexistence between a non-selective attractor state with low background activity with selective attractor states in which sub-groups of neurons fire at rates which are higher (but not much higher) than background rates. A recent detailed statistical analysis of the data seems however to challenge such attractor models: the data indicates that firing during persistent activity is highly irregular (with an average CV larger than 1), while models predict a more regular firing process (CV smaller than 1). We discuss here recent proposals that allow to reproduce this feature of the experiments. Frontiers Research Foundation 2008-07-15 /pmc/articles/PMC2570072/ /pubmed/18982114 http://dx.doi.org/10.3389/neuro.01.003.2008 Text en Copyright © 2008 Barbieri and Brunel. http://www.frontiersin.org/licenseagreement This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.
spellingShingle Neuroscience
Barbieri, Francesca
Brunel, Nicolas
Can Attractor Network Models Account for the Statistics of Firing During Persistent Activity in Prefrontal Cortex?
title Can Attractor Network Models Account for the Statistics of Firing During Persistent Activity in Prefrontal Cortex?
title_full Can Attractor Network Models Account for the Statistics of Firing During Persistent Activity in Prefrontal Cortex?
title_fullStr Can Attractor Network Models Account for the Statistics of Firing During Persistent Activity in Prefrontal Cortex?
title_full_unstemmed Can Attractor Network Models Account for the Statistics of Firing During Persistent Activity in Prefrontal Cortex?
title_short Can Attractor Network Models Account for the Statistics of Firing During Persistent Activity in Prefrontal Cortex?
title_sort can attractor network models account for the statistics of firing during persistent activity in prefrontal cortex?
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2570072/
https://www.ncbi.nlm.nih.gov/pubmed/18982114
http://dx.doi.org/10.3389/neuro.01.003.2008
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