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Transitions between asynchronous and synchronous states: a theory of correlations in small neural circuits
The study of correlations in neural circuits of different size, from the small size of cortical microcolumns to the large-scale organization of distributed networks studied with functional imaging, is a topic of central importance to systems neuroscience. However, a theory that explains how the para...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5770155/ https://www.ncbi.nlm.nih.gov/pubmed/29124505 http://dx.doi.org/10.1007/s10827-017-0667-3 |
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author | Fasoli, Diego Cattani, Anna Panzeri, Stefano |
author_facet | Fasoli, Diego Cattani, Anna Panzeri, Stefano |
author_sort | Fasoli, Diego |
collection | PubMed |
description | The study of correlations in neural circuits of different size, from the small size of cortical microcolumns to the large-scale organization of distributed networks studied with functional imaging, is a topic of central importance to systems neuroscience. However, a theory that explains how the parameters of mesoscopic networks composed of a few tens of neurons affect the underlying correlation structure is still missing. Here we consider a theory that can be applied to networks of arbitrary size with multiple populations of homogeneous fully-connected neurons, and we focus its analysis to a case of two populations of small size. We combine the analysis of local bifurcations of the dynamics of these networks with the analytical calculation of their cross-correlations. We study the correlation structure in different regimes, showing that a variation of the external stimuli causes the network to switch from asynchronous states, characterized by weak correlation and low variability, to synchronous states characterized by strong correlations and wide temporal fluctuations. We show that asynchronous states are generated by strong stimuli, while synchronous states occur through critical slowing down when the stimulus moves the network close to a local bifurcation. In particular, strongly positive correlations occur at the saddle-node and Andronov-Hopf bifurcations of the network, while strongly negative correlations occur when the network undergoes a spontaneous symmetry-breaking at the branching-point bifurcations. These results show how the correlation structure of firing-rate network models is strongly modulated by the external stimuli, even keeping the anatomical connections fixed. These results also suggest an effective mechanism through which biological networks may dynamically modulate the encoding and integration of sensory information. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10827-017-0667-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5770155 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-57701552018-01-29 Transitions between asynchronous and synchronous states: a theory of correlations in small neural circuits Fasoli, Diego Cattani, Anna Panzeri, Stefano J Comput Neurosci Article The study of correlations in neural circuits of different size, from the small size of cortical microcolumns to the large-scale organization of distributed networks studied with functional imaging, is a topic of central importance to systems neuroscience. However, a theory that explains how the parameters of mesoscopic networks composed of a few tens of neurons affect the underlying correlation structure is still missing. Here we consider a theory that can be applied to networks of arbitrary size with multiple populations of homogeneous fully-connected neurons, and we focus its analysis to a case of two populations of small size. We combine the analysis of local bifurcations of the dynamics of these networks with the analytical calculation of their cross-correlations. We study the correlation structure in different regimes, showing that a variation of the external stimuli causes the network to switch from asynchronous states, characterized by weak correlation and low variability, to synchronous states characterized by strong correlations and wide temporal fluctuations. We show that asynchronous states are generated by strong stimuli, while synchronous states occur through critical slowing down when the stimulus moves the network close to a local bifurcation. In particular, strongly positive correlations occur at the saddle-node and Andronov-Hopf bifurcations of the network, while strongly negative correlations occur when the network undergoes a spontaneous symmetry-breaking at the branching-point bifurcations. These results show how the correlation structure of firing-rate network models is strongly modulated by the external stimuli, even keeping the anatomical connections fixed. These results also suggest an effective mechanism through which biological networks may dynamically modulate the encoding and integration of sensory information. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10827-017-0667-3) contains supplementary material, which is available to authorized users. Springer US 2017-11-10 2018 /pmc/articles/PMC5770155/ /pubmed/29124505 http://dx.doi.org/10.1007/s10827-017-0667-3 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Fasoli, Diego Cattani, Anna Panzeri, Stefano Transitions between asynchronous and synchronous states: a theory of correlations in small neural circuits |
title | Transitions between asynchronous and synchronous states: a theory of correlations in small neural circuits |
title_full | Transitions between asynchronous and synchronous states: a theory of correlations in small neural circuits |
title_fullStr | Transitions between asynchronous and synchronous states: a theory of correlations in small neural circuits |
title_full_unstemmed | Transitions between asynchronous and synchronous states: a theory of correlations in small neural circuits |
title_short | Transitions between asynchronous and synchronous states: a theory of correlations in small neural circuits |
title_sort | transitions between asynchronous and synchronous states: a theory of correlations in small neural circuits |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5770155/ https://www.ncbi.nlm.nih.gov/pubmed/29124505 http://dx.doi.org/10.1007/s10827-017-0667-3 |
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