Cargando…

Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states

The dynamics of neuronal networks connected by synaptic dynamics can sustain long periods of depolarization that can last for hundreds of milliseconds such as Up states recorded during sleep or anesthesia. Yet the underlying mechanism driving these periods remain unclear. We show here within a mean-...

Descripción completa

Detalles Bibliográficos
Autores principales: Dao Duc, Khanh, Parutto, Pierre, Chen, Xiaowei, Epsztein, Jérôme, Konnerth, Arthur, Holcman, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4518200/
https://www.ncbi.nlm.nih.gov/pubmed/26283956
http://dx.doi.org/10.3389/fncom.2015.00096
_version_ 1782383303566819328
author Dao Duc, Khanh
Parutto, Pierre
Chen, Xiaowei
Epsztein, Jérôme
Konnerth, Arthur
Holcman, David
author_facet Dao Duc, Khanh
Parutto, Pierre
Chen, Xiaowei
Epsztein, Jérôme
Konnerth, Arthur
Holcman, David
author_sort Dao Duc, Khanh
collection PubMed
description The dynamics of neuronal networks connected by synaptic dynamics can sustain long periods of depolarization that can last for hundreds of milliseconds such as Up states recorded during sleep or anesthesia. Yet the underlying mechanism driving these periods remain unclear. We show here within a mean-field model that the residence time of the neuronal membrane potential in cortical Up states does not follow a Poissonian law, but presents several peaks. Furthermore, the present modeling approach allows extracting some information about the neuronal network connectivity from the time distribution histogram. Based on a synaptic-depression model, we find that these peaks, that can be observed in histograms of patch-clamp recordings are not artifacts of electrophysiological measurements, but rather are an inherent property of the network dynamics. Analysis of the equations reveals a stable focus located close to the unstable limit cycle, delimiting a region that defines the Up state. The model further shows that the peaks observed in the Up state time distribution are due to winding around the focus before escaping from the basin of attraction. Finally, we use in vivo recordings of intracellular membrane potential and we recover from the peak distribution, some information about the network connectivity. We conclude that it is possible to recover the network connectivity from the distribution of times that the neuronal membrane voltage spends in Up states.
format Online
Article
Text
id pubmed-4518200
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-45182002015-08-17 Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states Dao Duc, Khanh Parutto, Pierre Chen, Xiaowei Epsztein, Jérôme Konnerth, Arthur Holcman, David Front Comput Neurosci Neuroscience The dynamics of neuronal networks connected by synaptic dynamics can sustain long periods of depolarization that can last for hundreds of milliseconds such as Up states recorded during sleep or anesthesia. Yet the underlying mechanism driving these periods remain unclear. We show here within a mean-field model that the residence time of the neuronal membrane potential in cortical Up states does not follow a Poissonian law, but presents several peaks. Furthermore, the present modeling approach allows extracting some information about the neuronal network connectivity from the time distribution histogram. Based on a synaptic-depression model, we find that these peaks, that can be observed in histograms of patch-clamp recordings are not artifacts of electrophysiological measurements, but rather are an inherent property of the network dynamics. Analysis of the equations reveals a stable focus located close to the unstable limit cycle, delimiting a region that defines the Up state. The model further shows that the peaks observed in the Up state time distribution are due to winding around the focus before escaping from the basin of attraction. Finally, we use in vivo recordings of intracellular membrane potential and we recover from the peak distribution, some information about the network connectivity. We conclude that it is possible to recover the network connectivity from the distribution of times that the neuronal membrane voltage spends in Up states. Frontiers Media S.A. 2015-07-29 /pmc/articles/PMC4518200/ /pubmed/26283956 http://dx.doi.org/10.3389/fncom.2015.00096 Text en Copyright © 2015 Dao Duc, Parutto, Chen, Epsztein, Konnerth and Holcman. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Dao Duc, Khanh
Parutto, Pierre
Chen, Xiaowei
Epsztein, Jérôme
Konnerth, Arthur
Holcman, David
Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states
title Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states
title_full Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states
title_fullStr Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states
title_full_unstemmed Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states
title_short Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states
title_sort synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in up states
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4518200/
https://www.ncbi.nlm.nih.gov/pubmed/26283956
http://dx.doi.org/10.3389/fncom.2015.00096
work_keys_str_mv AT daoduckhanh synapticdynamicsandneuronalnetworkconnectivityarereflectedinthedistributionoftimesinupstates
AT paruttopierre synapticdynamicsandneuronalnetworkconnectivityarereflectedinthedistributionoftimesinupstates
AT chenxiaowei synapticdynamicsandneuronalnetworkconnectivityarereflectedinthedistributionoftimesinupstates
AT epszteinjerome synapticdynamicsandneuronalnetworkconnectivityarereflectedinthedistributionoftimesinupstates
AT konnertharthur synapticdynamicsandneuronalnetworkconnectivityarereflectedinthedistributionoftimesinupstates
AT holcmandavid synapticdynamicsandneuronalnetworkconnectivityarereflectedinthedistributionoftimesinupstates