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Synaptic Impairment and Robustness of Excitatory Neuronal Networks with Different Topologies
Synaptic deficiencies are a known hallmark of neurodegenerative diseases, but the diagnosis of impaired synapses on the cellular level is not an easy task. Nonetheless, changes in the system-level dynamics of neuronal networks with damaged synapses can be detected using techniques that do not requir...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5468411/ https://www.ncbi.nlm.nih.gov/pubmed/28659765 http://dx.doi.org/10.3389/fncir.2017.00038 |
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author | Mirzakhalili, Ehsan Gourgou, Eleni Booth, Victoria Epureanu, Bogdan |
author_facet | Mirzakhalili, Ehsan Gourgou, Eleni Booth, Victoria Epureanu, Bogdan |
author_sort | Mirzakhalili, Ehsan |
collection | PubMed |
description | Synaptic deficiencies are a known hallmark of neurodegenerative diseases, but the diagnosis of impaired synapses on the cellular level is not an easy task. Nonetheless, changes in the system-level dynamics of neuronal networks with damaged synapses can be detected using techniques that do not require high spatial resolution. This paper investigates how the structure/topology of neuronal networks influences their dynamics when they suffer from synaptic loss. We study different neuronal network structures/topologies by specifying their degree distributions. The modes of the degree distribution can be used to construct networks that consist of rich clubs and resemble small world networks, as well. We define two dynamical metrics to compare the activity of networks with different structures: persistent activity (namely, the self-sustained activity of the network upon removal of the initial stimulus) and quality of activity (namely, percentage of neurons that participate in the persistent activity of the network). Our results show that synaptic loss affects the persistent activity of networks with bimodal degree distributions less than it affects random networks. The robustness of neuronal networks enhances when the distance between the modes of the degree distribution increases, suggesting that the rich clubs of networks with distinct modes keep the whole network active. In addition, a tradeoff is observed between the quality of activity and the persistent activity. For a range of distributions, both of these dynamical metrics are considerably high for networks with bimodal degree distribution compared to random networks. We also propose three different scenarios of synaptic impairment, which may correspond to different pathological or biological conditions. Regardless of the network structure/topology, results demonstrate that synaptic loss has more severe effects on the activity of the network when impairments are correlated with the activity of the neurons. |
format | Online Article Text |
id | pubmed-5468411 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-54684112017-06-28 Synaptic Impairment and Robustness of Excitatory Neuronal Networks with Different Topologies Mirzakhalili, Ehsan Gourgou, Eleni Booth, Victoria Epureanu, Bogdan Front Neural Circuits Neuroscience Synaptic deficiencies are a known hallmark of neurodegenerative diseases, but the diagnosis of impaired synapses on the cellular level is not an easy task. Nonetheless, changes in the system-level dynamics of neuronal networks with damaged synapses can be detected using techniques that do not require high spatial resolution. This paper investigates how the structure/topology of neuronal networks influences their dynamics when they suffer from synaptic loss. We study different neuronal network structures/topologies by specifying their degree distributions. The modes of the degree distribution can be used to construct networks that consist of rich clubs and resemble small world networks, as well. We define two dynamical metrics to compare the activity of networks with different structures: persistent activity (namely, the self-sustained activity of the network upon removal of the initial stimulus) and quality of activity (namely, percentage of neurons that participate in the persistent activity of the network). Our results show that synaptic loss affects the persistent activity of networks with bimodal degree distributions less than it affects random networks. The robustness of neuronal networks enhances when the distance between the modes of the degree distribution increases, suggesting that the rich clubs of networks with distinct modes keep the whole network active. In addition, a tradeoff is observed between the quality of activity and the persistent activity. For a range of distributions, both of these dynamical metrics are considerably high for networks with bimodal degree distribution compared to random networks. We also propose three different scenarios of synaptic impairment, which may correspond to different pathological or biological conditions. Regardless of the network structure/topology, results demonstrate that synaptic loss has more severe effects on the activity of the network when impairments are correlated with the activity of the neurons. Frontiers Media S.A. 2017-06-13 /pmc/articles/PMC5468411/ /pubmed/28659765 http://dx.doi.org/10.3389/fncir.2017.00038 Text en Copyright © 2017 Mirzakhalili, Gourgou, Booth and Epureanu. 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) 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 Mirzakhalili, Ehsan Gourgou, Eleni Booth, Victoria Epureanu, Bogdan Synaptic Impairment and Robustness of Excitatory Neuronal Networks with Different Topologies |
title | Synaptic Impairment and Robustness of Excitatory Neuronal Networks with Different Topologies |
title_full | Synaptic Impairment and Robustness of Excitatory Neuronal Networks with Different Topologies |
title_fullStr | Synaptic Impairment and Robustness of Excitatory Neuronal Networks with Different Topologies |
title_full_unstemmed | Synaptic Impairment and Robustness of Excitatory Neuronal Networks with Different Topologies |
title_short | Synaptic Impairment and Robustness of Excitatory Neuronal Networks with Different Topologies |
title_sort | synaptic impairment and robustness of excitatory neuronal networks with different topologies |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5468411/ https://www.ncbi.nlm.nih.gov/pubmed/28659765 http://dx.doi.org/10.3389/fncir.2017.00038 |
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