Evoking complex neuronal networks by stimulating a single neuron
Mengjiao Chen, Weijie Lin, Hengtong Wang, Wei Ren, and Xingang Wang

TL;DR
This paper investigates how stimulating a single neuron in complex networks can induce transitions between resting and firing states, revealing the roles of stimulus intensity and coupling strength in network dynamics.
Contribution
It introduces a detailed analysis of network responses to single-neuron stimulation, including a new effective stimulus coefficient and bifurcation analysis, enhancing understanding of neuronal network control.
Findings
Firing regions depend on stimulus intensity and coupling strength.
Weak coupling expands and disconnects firing regions.
Effective stimulus shifts with stimulation intensity and coupling strength.
Abstract
The dynamical responses of complex neuronal networks to external stimulus injected on a \emph{single} neuron are investigated. Stimulating the largest-degree neuron in the network, it is found that as the intensity of the stimulus increases, the network will be transiting from the resting to firing states and then restoring to the resting state, showing a bounded firing region in the parameter space. Furthermore, it is found that as the coupling strength decreases, the firing region is gradually expanded and, at the weak couplings, separated into disconnected subregions. By a simplified network model, we conduct a detail analysis on the bifurcation diagram of the network dynamics in the two-dimensional parameter space spanned by stimulating intensity and coupling strength, and, by introducing a new coefficient named effective stimulus, explore the mechanisms of the modified firing…
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Taxonomy
Topicsstochastic dynamics and bifurcation · Neural dynamics and brain function · Nonlinear Dynamics and Pattern Formation
