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Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons

Experimental and numerical studies have revealed that isolated populations of oscillatory neurons can spontaneously synchronize and generate periodic bursts involving the whole network. Such a behavior has notably been observed for cultured neurons in rodent's cortex or hippocampus. We show her...

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Autores principales: Fardet, Tanguy, Ballandras, Mathieu, Bottani, Samuel, Métens, Stéphane, Monceau, Pascal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5808224/
https://www.ncbi.nlm.nih.gov/pubmed/29467607
http://dx.doi.org/10.3389/fnins.2018.00041
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author Fardet, Tanguy
Ballandras, Mathieu
Bottani, Samuel
Métens, Stéphane
Monceau, Pascal
author_facet Fardet, Tanguy
Ballandras, Mathieu
Bottani, Samuel
Métens, Stéphane
Monceau, Pascal
author_sort Fardet, Tanguy
collection PubMed
description Experimental and numerical studies have revealed that isolated populations of oscillatory neurons can spontaneously synchronize and generate periodic bursts involving the whole network. Such a behavior has notably been observed for cultured neurons in rodent's cortex or hippocampus. We show here that a sufficient condition for this network bursting is the presence of an excitatory population of oscillatory neurons which displays spike-driven adaptation. We provide an analytic model to analyze network bursts generated by coupled adaptive exponential integrate-and-fire neurons. We show that, for strong synaptic coupling, intrinsically tonic spiking neurons evolve to reach a synchronized intermittent bursting state. The presence of inhibitory neurons or plastic synapses can then modulate this dynamics in many ways but is not necessary for its appearance. Thanks to a simple self-consistent equation, our model gives an intuitive and semi-quantitative tool to understand the bursting behavior. Furthermore, it suggests that after-hyperpolarization currents are sufficient to explain bursting termination. Through a thorough mapping between the theoretical parameters and ion-channel properties, we discuss the biological mechanisms that could be involved and the relevance of the explored parameter-space. Such an insight enables us to propose experimentally-testable predictions regarding how blocking fast, medium or slow after-hyperpolarization channels would affect the firing rate and burst duration, as well as the interburst interval.
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spelling pubmed-58082242018-02-21 Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons Fardet, Tanguy Ballandras, Mathieu Bottani, Samuel Métens, Stéphane Monceau, Pascal Front Neurosci Neuroscience Experimental and numerical studies have revealed that isolated populations of oscillatory neurons can spontaneously synchronize and generate periodic bursts involving the whole network. Such a behavior has notably been observed for cultured neurons in rodent's cortex or hippocampus. We show here that a sufficient condition for this network bursting is the presence of an excitatory population of oscillatory neurons which displays spike-driven adaptation. We provide an analytic model to analyze network bursts generated by coupled adaptive exponential integrate-and-fire neurons. We show that, for strong synaptic coupling, intrinsically tonic spiking neurons evolve to reach a synchronized intermittent bursting state. The presence of inhibitory neurons or plastic synapses can then modulate this dynamics in many ways but is not necessary for its appearance. Thanks to a simple self-consistent equation, our model gives an intuitive and semi-quantitative tool to understand the bursting behavior. Furthermore, it suggests that after-hyperpolarization currents are sufficient to explain bursting termination. Through a thorough mapping between the theoretical parameters and ion-channel properties, we discuss the biological mechanisms that could be involved and the relevance of the explored parameter-space. Such an insight enables us to propose experimentally-testable predictions regarding how blocking fast, medium or slow after-hyperpolarization channels would affect the firing rate and burst duration, as well as the interburst interval. Frontiers Media S.A. 2018-02-06 /pmc/articles/PMC5808224/ /pubmed/29467607 http://dx.doi.org/10.3389/fnins.2018.00041 Text en Copyright © 2018 Fardet, Ballandras, Bottani, Métens and Monceau. 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 or reproduction in other forums is permitted, provided the original author(s) and the copyright owner 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
Fardet, Tanguy
Ballandras, Mathieu
Bottani, Samuel
Métens, Stéphane
Monceau, Pascal
Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons
title Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons
title_full Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons
title_fullStr Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons
title_full_unstemmed Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons
title_short Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons
title_sort understanding the generation of network bursts by adaptive oscillatory neurons
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5808224/
https://www.ncbi.nlm.nih.gov/pubmed/29467607
http://dx.doi.org/10.3389/fnins.2018.00041
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