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

Authors :
Subrata Ghosh
Argha Mondal
Peng Ji
Arindam Mishra
Syamal K. Dana
Chris G. Antonopoulos
Chittaranjan Hens
Source :
Frontiers in Computational Neuroscience, Vol 14 (2020)
Publication Year :
2020
Publisher :
Frontiers Media S.A., 2020.

Abstract

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.

Details

Language :
English
ISSN :
16625188
Volume :
14
Database :
Directory of Open Access Journals
Journal :
Frontiers in Computational Neuroscience
Publication Type :
Academic Journal
Accession number :
edsdoj.60015b65200c43288f6430344f3aaffb
Document Type :
article
Full Text :
https://doi.org/10.3389/fncom.2020.00049