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Network and cellular mechanisms underlying heterogeneous excitatory/inhibitory balanced states.

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Title: Network and cellular mechanisms underlying heterogeneous excitatory/inhibitory balanced states.
Authors: Wu, Jiaxing (AUTHOR), Aton, Sara J. (AUTHOR), Booth, Victoria (AUTHOR), Zochowski, Michal (AUTHOR)
Source: European Journal of Neuroscience. Apr2020, Vol. 51 Issue 7, p1624-1641. 18p. 2 Diagrams, 7 Graphs.
Subjects: Artificial neural networks, Inhibitory postsynaptic potential, Brain diseases
Abstract: Recent work has explored spatiotemporal relationships between excitatory (E) and inhibitory (I) signaling within neural networks, and the effect of these relationships on network activity patterns. Data from these studies have indicated that excitation and inhibition are maintained at a similar level across long time periods and that excitatory and inhibitory currents may be tightly synchronized. Disruption of this balance—leading to an aberrant E/I ratio—is implicated in various brain pathologies. However, a thorough characterization of the relationship between E and I currents in experimental settings is largely impossible, due to their tight regulation at multiple cellular and network levels. Here, we use biophysical neural network models to investigate the emergence and properties of balanced states by heterogeneous mechanisms. Our results show that a network can homeostatically regulate the E/I ratio through interactions among multiple cellular and network factors, including average firing rates, synaptic weights and average neural depolarization levels in excitatory/inhibitory populations. Complex and competing interactions between firing rates and depolarization levels allow these factors to alternately dominate network dynamics in different synaptic weight regimes. This leads to the emergence of distinct mechanisms responsible for determining a balanced state and its dynamical correlate. Our analysis provides a comprehensive picture of how E/I ratio changes when manipulating specific network properties, and identifies the mechanisms regulating E/I balance. These results provide a framework to explain the diverse, and in some cases, contradictory experimental observations on the E/I state in different brain states and conditions. [ABSTRACT FROM AUTHOR]
Copyright of European Journal of Neuroscience is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Label: Title
  Group: Ti
  Data: Network and cellular mechanisms underlying heterogeneous excitatory/inhibitory balanced states.
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  Data: <searchLink fieldCode="AR" term="%22Wu%2C+Jiaxing%22">Wu, Jiaxing</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Aton%2C+Sara+J%2E%22">Aton, Sara J.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Booth%2C+Victoria%22">Booth, Victoria</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zochowski%2C+Michal%22">Zochowski, Michal</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22European+Journal+of+Neuroscience%22">European Journal of Neuroscience</searchLink>. Apr2020, Vol. 51 Issue 7, p1624-1641. 18p. 2 Diagrams, 7 Graphs.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Inhibitory+postsynaptic+potential%22">Inhibitory postsynaptic potential</searchLink><br /><searchLink fieldCode="DE" term="%22Brain+diseases%22">Brain diseases</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Recent work has explored spatiotemporal relationships between excitatory (E) and inhibitory (I) signaling within neural networks, and the effect of these relationships on network activity patterns. Data from these studies have indicated that excitation and inhibition are maintained at a similar level across long time periods and that excitatory and inhibitory currents may be tightly synchronized. Disruption of this balance—leading to an aberrant E/I ratio—is implicated in various brain pathologies. However, a thorough characterization of the relationship between E and I currents in experimental settings is largely impossible, due to their tight regulation at multiple cellular and network levels. Here, we use biophysical neural network models to investigate the emergence and properties of balanced states by heterogeneous mechanisms. Our results show that a network can homeostatically regulate the E/I ratio through interactions among multiple cellular and network factors, including average firing rates, synaptic weights and average neural depolarization levels in excitatory/inhibitory populations. Complex and competing interactions between firing rates and depolarization levels allow these factors to alternately dominate network dynamics in different synaptic weight regimes. This leads to the emergence of distinct mechanisms responsible for determining a balanced state and its dynamical correlate. Our analysis provides a comprehensive picture of how E/I ratio changes when manipulating specific network properties, and identifies the mechanisms regulating E/I balance. These results provide a framework to explain the diverse, and in some cases, contradictory experimental observations on the E/I state in different brain states and conditions. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of European Journal of Neuroscience is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/ejn.14669
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      – Code: eng
        Text: English
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        PageCount: 18
        StartPage: 1624
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        Type: general
      – SubjectFull: Inhibitory postsynaptic potential
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      – SubjectFull: Brain diseases
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              Text: Apr2020
              Type: published
              Y: 2020
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