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Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics
Neuronal firing and neuron-to-neuron synaptic wiring are currently widely described as orchestrated by astrocytes—elaborately ramified glial cells tiling the cortical and hippocampal space into non-overlapping domains, each covering hundreds of individual dendrites and hundreds thousands synapses. A...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7973220/ https://www.ncbi.nlm.nih.gov/pubmed/33746715 http://dx.doi.org/10.3389/fncel.2021.645068 |
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author | Verisokin, Andrey Yu. Verveyko, Darya V. Postnov, Dmitry E. Brazhe, Alexey R. |
author_facet | Verisokin, Andrey Yu. Verveyko, Darya V. Postnov, Dmitry E. Brazhe, Alexey R. |
author_sort | Verisokin, Andrey Yu. |
collection | PubMed |
description | Neuronal firing and neuron-to-neuron synaptic wiring are currently widely described as orchestrated by astrocytes—elaborately ramified glial cells tiling the cortical and hippocampal space into non-overlapping domains, each covering hundreds of individual dendrites and hundreds thousands synapses. A key component to astrocytic signaling is the dynamics of cytosolic Ca(2+) which displays multiscale spatiotemporal patterns from short confined elemental Ca(2+) events (puffs) to Ca(2+) waves expanding through many cells. Here, we synthesize the current understanding of astrocyte morphology, coupling local synaptic activity to astrocytic Ca(2+) in perisynaptic astrocytic processes and morphology-defined mechanisms of Ca(2+) regulation in a distributed model. To this end, we build simplified realistic data-driven spatial network templates and compile model equations as defined by local cell morphology. The input to the model is spatially uncorrelated stochastic synaptic activity. The proposed modeling approach is validated by statistics of simulated Ca(2+) transients at a single cell level. In multicellular templates we observe regular sequences of cell entrainment in Ca(2+) waves, as a result of interplay between stochastic input and morphology variability between individual astrocytes. Our approach adds spatial dimension to the existing astrocyte models by employment of realistic morphology while retaining enough flexibility and scalability to be embedded in multiscale heterocellular models of neural tissue. We conclude that the proposed approach provides a useful description of neuron-driven Ca(2+)-activity in the astrocyte syncytium. |
format | Online Article Text |
id | pubmed-7973220 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79732202021-03-20 Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics Verisokin, Andrey Yu. Verveyko, Darya V. Postnov, Dmitry E. Brazhe, Alexey R. Front Cell Neurosci Cellular Neuroscience Neuronal firing and neuron-to-neuron synaptic wiring are currently widely described as orchestrated by astrocytes—elaborately ramified glial cells tiling the cortical and hippocampal space into non-overlapping domains, each covering hundreds of individual dendrites and hundreds thousands synapses. A key component to astrocytic signaling is the dynamics of cytosolic Ca(2+) which displays multiscale spatiotemporal patterns from short confined elemental Ca(2+) events (puffs) to Ca(2+) waves expanding through many cells. Here, we synthesize the current understanding of astrocyte morphology, coupling local synaptic activity to astrocytic Ca(2+) in perisynaptic astrocytic processes and morphology-defined mechanisms of Ca(2+) regulation in a distributed model. To this end, we build simplified realistic data-driven spatial network templates and compile model equations as defined by local cell morphology. The input to the model is spatially uncorrelated stochastic synaptic activity. The proposed modeling approach is validated by statistics of simulated Ca(2+) transients at a single cell level. In multicellular templates we observe regular sequences of cell entrainment in Ca(2+) waves, as a result of interplay between stochastic input and morphology variability between individual astrocytes. Our approach adds spatial dimension to the existing astrocyte models by employment of realistic morphology while retaining enough flexibility and scalability to be embedded in multiscale heterocellular models of neural tissue. We conclude that the proposed approach provides a useful description of neuron-driven Ca(2+)-activity in the astrocyte syncytium. Frontiers Media S.A. 2021-03-05 /pmc/articles/PMC7973220/ /pubmed/33746715 http://dx.doi.org/10.3389/fncel.2021.645068 Text en Copyright © 2021 Verisokin, Verveyko, Postnov and Brazhe. 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(s) 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 | Cellular Neuroscience Verisokin, Andrey Yu. Verveyko, Darya V. Postnov, Dmitry E. Brazhe, Alexey R. Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics |
title | Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics |
title_full | Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics |
title_fullStr | Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics |
title_full_unstemmed | Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics |
title_short | Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics |
title_sort | modeling of astrocyte networks: toward realistic topology and dynamics |
topic | Cellular Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7973220/ https://www.ncbi.nlm.nih.gov/pubmed/33746715 http://dx.doi.org/10.3389/fncel.2021.645068 |
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