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

Subrata Ghosh, Argha Mondal, Peng Ji, Arindam Mishra, Syamal K. Dana, Chris G. Antonopoulos, Chittaranjan Hens

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

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.

Original languageEnglish
Article number49
JournalFrontiers in Computational Neuroscience
Volume14
DOIs
StatePublished - 8 Jun 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© Copyright © 2020 Ghosh, Mondal, Ji, Mishra, Dana, Antonopoulos and Hens.

Funding

Funding. CH was supported by the INSPIRE-Faculty grant (code: IFA17-PH193). PJ was funded by Natural Science Foundation of Shanghai, the program for Professor of Special Appointment (Eastern Scholar) and by NSFC 269 (11701096).

FundersFunder number
Natural Science Foundation of Shanghai
National Natural Science Foundation of China11701096, 269

    Keywords

    • Izhikevich neuron model
    • bicurcation scenaria
    • electrical coupling
    • excitable neurons
    • mixed mode bursting oscillations (MMBOs)
    • mixed mode oscillations (MMOs)
    • random networks

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