Stochastic Resonance in Excitable Neuronal System with Phase-Noise

Author(s):  
Xiaoming Liang ◽  
Liang Zhao
2019 ◽  
Vol 29 (14) ◽  
pp. 1950202 ◽  
Author(s):  
Lianghui Qu ◽  
Lin Du ◽  
Honghui Zhang ◽  
Zilu Cao ◽  
Zichen Deng

To explore the feasibility of physiological manipulation of autaptic structures, the effects of autaptic connections on an FHN-ML neuronal system with phase noise stimulation are studied systematically. Firstly, according to the dynamic analysis of the FHN-ML neuron model, a saddle-node bifurcation can occur on an invariant circle. Under the action of external oscillatory current with phase noise, the neuronal firing activity is sensitive to phase noise with less intensity, and an appropriate noise intensity can induce a significant stochastic resonance phenomenon. Secondly, the chemical autaptic function can effectively regulate the neuronal discharge activity. An inhibitory autapse can not only induce the transition from depolarized resting to periodic spiking, but can also induce the FHN-ML neuron suppressed by strong phase noise to generate a pronounced intermittent high-level burst-like discharge mode when the autaptic conductance is greater than 0.1. Finally, for a two-dimensional regular FHN-ML neuronal network, a small amount of autaptic structures can induce some special waveforms to restore the propagation of nerve impulses interrupted by phase noise disturbance. This indicates the significant regulation of autapses on spatial patterns of the FHN-ML neuronal network. The study can provide some theoretical guidance for building autaptic structures in local areas to modulate the dynamic behaviors of biological neuronal systems.


2019 ◽  
Vol 88 (6) ◽  
pp. 063001 ◽  
Author(s):  
Jong-Hoon Huh ◽  
Yoshimitsu Yano ◽  
Naoto Miyagawa

2019 ◽  
Vol 33 (26) ◽  
pp. 1950302
Author(s):  
Xiao Li Yang ◽  
Xiao Qiang Liu

Through introducing the ingredients of electromagnetic induction and coupled time delay into the original Fitzhugh–Nagumo (FHN) neuronal network, the dynamics of stochastic resonance in a model of modified FHN neuronal network in the environment of phase noise is explored by numerical simulations in this study. On one hand, we demonstrate that the phenomenon of stochastic resonance can appear when the intensity of phase noise is appropriately adjusted, which is further verified to be robust to the edge-added probability of small-world network. Moreover, under the influence of electromagnetic induction, the phase noise-induced resonance response is suppressed, meanwhile, a large noise intensity is required to induce stochastic resonance as the feedback gain of induced current increases. On the other hand, when the coupled time delay is incorporated into this model, the results indicate that the properly tuned time delay can induce multiple stochastic resonances in this neuronal network. However, the phenomenon of multiple stochastic resonances is found to be restrained upon increasing feedback gain of induced current. Surprisingly, by changing the period of phase noise, multiple stochastic resonances can still emerge when the coupled time delay is appropriately tuned to be integer multiples of the period of phase noise.


2005 ◽  
Vol 94 (2) ◽  
pp. 118-127 ◽  
Author(s):  
Matteo Giannì ◽  
Micaela Liberti ◽  
Francesca Apollonio ◽  
Guglielmo D’Inzeo

2000 ◽  
Vol 61 (1) ◽  
pp. 940-943 ◽  
Author(s):  
François Chapeau-Blondeau

2011 ◽  
Vol 84 (3) ◽  
Author(s):  
Xiaoming Liang ◽  
Liang Zhao ◽  
Zonghua Liu
Keyword(s):  

1990 ◽  
Vol 42 (11) ◽  
pp. 6651-6659 ◽  
Author(s):  
A. A. Rangwala ◽  
K. Wódkiewicz ◽  
C. Su

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