Noise-induced network bursts and coherence in a calcium-mediated neural network. Issue 12 (December 2021)

• Record Type: Journal Article
• Authors: Yu, Na; Jagdev, Gurpreet; Morgovsky, Michelle
• Is Part Of: Heliyon. Volume 7:Issue 12(2021)
• Publication Date: 2021-12
• Subjects: Noise-induced burst firing -- Population bursts -- Coherence resonance -- Heterogeneous network; Research -- Periodicals; Medical sciences -- Periodicals; Natural history -- Periodicals; Social sciences -- Periodicals; Earth sciences -- Periodicals; Physical sciences -- Periodicals; 507.2
• DOI: 10.1016/j.heliyon.2021.e08612
• Languages: English
• ISSNs: 2405-8440

Abstract

Abstract: Noise-induced population bursting has been widely identified to play important roles in information processes. We construct a mathematical model for a random and sparse heterogeneous neural network where bursting can be induced from a resting state by a global stochastic stimulus. Importantly, the noise-induced bursting dynamics of this network are mediated by calcium conductance. We use two spectral measures to evaluate network coherence in the context of the network bursts, the spike trains of all neurons, and the individual bursts of all neurons. Our results show that the coherence of the network is optimized by an optimal level of the stochastic stimulus, which is known as coherence resonance (CR). We also demonstrate that the interplay of the calcium conductance and noise intensity can modify the degree of CR. Abstract : Noise-induced burst firing; Population bursts; Coherence resonance; Heterogeneous network