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Emergence of Mixed Mode Oscillations in Random Networks of Diverse Excitable Neurons: The Role of Neighbors and Electrical Coupling

In this paper, we focus on the emergence of diverse neuronal oscillations arising in a mixed population of neurons with different excitability properties. These properties produce mixed mode oscillations (MMOs) characterized by the combination of large amplitudes and alternate subthreshold or small...

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Autores principales: Ghosh, Subrata, Mondal, Argha, Ji, Peng, Mishra, Arindam, Dana, Syamal K., Antonopoulos, Chris G., Hens, Chittaranjan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7294985/
https://www.ncbi.nlm.nih.gov/pubmed/32581757
http://dx.doi.org/10.3389/fncom.2020.00049
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author Ghosh, Subrata
Mondal, Argha
Ji, Peng
Mishra, Arindam
Dana, Syamal K.
Antonopoulos, Chris G.
Hens, Chittaranjan
author_facet Ghosh, Subrata
Mondal, Argha
Ji, Peng
Mishra, Arindam
Dana, Syamal K.
Antonopoulos, Chris G.
Hens, Chittaranjan
author_sort Ghosh, Subrata
collection PubMed
description In this paper, we focus on the emergence of diverse neuronal oscillations arising in a mixed population of neurons with different excitability properties. These properties produce mixed mode oscillations (MMOs) characterized by the combination of large amplitudes and alternate subthreshold or small amplitude oscillations. Considering the biophysically plausible, Izhikevich neuron model, we demonstrate that various MMOs, including MMBOs (mixed mode bursting oscillations) and synchronized tonic spiking appear in a randomly connected network of neurons, where a fraction of them is in a quiescent (silent) state and the rest in self-oscillatory (firing) states. We show that MMOs and other patterns of neural activity depend on the number of oscillatory neighbors of quiescent nodes and on electrical coupling strengths. Our results are verified by constructing a reduced-order network model and supported by systematic bifurcation diagrams as well as for a small-world network. Our results suggest that, for weak couplings, MMOs appear due to the de-synchronization of a large number of quiescent neurons in the networks. The quiescent neurons together with the firing neurons produce high frequency oscillations and bursting activity. The overarching goal is to uncover a favorable network architecture and suitable parameter spaces where Izhikevich model neurons generate diverse responses ranging from MMOs to tonic spiking.
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spelling pubmed-72949852020-06-23 Emergence of Mixed Mode Oscillations in Random Networks of Diverse Excitable Neurons: The Role of Neighbors and Electrical Coupling Ghosh, Subrata Mondal, Argha Ji, Peng Mishra, Arindam Dana, Syamal K. Antonopoulos, Chris G. Hens, Chittaranjan Front Comput Neurosci Neuroscience In this paper, we focus on the emergence of diverse neuronal oscillations arising in a mixed population of neurons with different excitability properties. These properties produce mixed mode oscillations (MMOs) characterized by the combination of large amplitudes and alternate subthreshold or small amplitude oscillations. Considering the biophysically plausible, Izhikevich neuron model, we demonstrate that various MMOs, including MMBOs (mixed mode bursting oscillations) and synchronized tonic spiking appear in a randomly connected network of neurons, where a fraction of them is in a quiescent (silent) state and the rest in self-oscillatory (firing) states. We show that MMOs and other patterns of neural activity depend on the number of oscillatory neighbors of quiescent nodes and on electrical coupling strengths. Our results are verified by constructing a reduced-order network model and supported by systematic bifurcation diagrams as well as for a small-world network. Our results suggest that, for weak couplings, MMOs appear due to the de-synchronization of a large number of quiescent neurons in the networks. The quiescent neurons together with the firing neurons produce high frequency oscillations and bursting activity. The overarching goal is to uncover a favorable network architecture and suitable parameter spaces where Izhikevich model neurons generate diverse responses ranging from MMOs to tonic spiking. Frontiers Media S.A. 2020-06-08 /pmc/articles/PMC7294985/ /pubmed/32581757 http://dx.doi.org/10.3389/fncom.2020.00049 Text en Copyright © 2020 Ghosh, Mondal, Ji, Mishra, Dana, Antonopoulos and Hens. 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 Neuroscience
Ghosh, Subrata
Mondal, Argha
Ji, Peng
Mishra, Arindam
Dana, Syamal K.
Antonopoulos, Chris G.
Hens, Chittaranjan
Emergence of Mixed Mode Oscillations in Random Networks of Diverse Excitable Neurons: The Role of Neighbors and Electrical Coupling
title Emergence of Mixed Mode Oscillations in Random Networks of Diverse Excitable Neurons: The Role of Neighbors and Electrical Coupling
title_full Emergence of Mixed Mode Oscillations in Random Networks of Diverse Excitable Neurons: The Role of Neighbors and Electrical Coupling
title_fullStr Emergence of Mixed Mode Oscillations in Random Networks of Diverse Excitable Neurons: The Role of Neighbors and Electrical Coupling
title_full_unstemmed Emergence of Mixed Mode Oscillations in Random Networks of Diverse Excitable Neurons: The Role of Neighbors and Electrical Coupling
title_short Emergence of Mixed Mode Oscillations in Random Networks of Diverse Excitable Neurons: The Role of Neighbors and Electrical Coupling
title_sort emergence of mixed mode oscillations in random networks of diverse excitable neurons: the role of neighbors and electrical coupling
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7294985/
https://www.ncbi.nlm.nih.gov/pubmed/32581757
http://dx.doi.org/10.3389/fncom.2020.00049
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