DocumentCode
3070748
Title
Coherent oscillations in minimal neural network of excitable systems induced by noise and influenced by time delay
Author
Vasovic, Nebojsa ; Buric, N. ; Grozdanovic, I. ; Todorovic, Kristina ; Samcovic, Andreja
Author_Institution
Dept. of Appl. Math., Univ. of Belgrade, Belgrade, Serbia
fYear
2012
fDate
20-22 Sept. 2012
Firstpage
35
Lastpage
39
Abstract
Influence of small time-delays in coupling between noisy excitable systems on the coherence resonance and self-induced stochastic resonance is studied. Parameters of delayed coupled deterministic excitable units are chosen such that the system has only one attractor, namely the stationary state, for any value of the coupling and the time-lag. Addition of white noise induces qualitatively different types of coherent oscillations, and we analyzed the influence of coupling time-delay on the properties of these coherent oscillations. The main conclusion is that time-lag τ ≥ 1, but still smaller than the refractory period, and sufficiently strong coupling drastically change signal-to-noise ratio in the quantitative and qualitative way. An interval of noise values implies quite large signal to noise ratio and different types of noise induced coherence are greatly enhanced. We also observed coincident spiking for small noise intensity and time-lag proportional to the inter-spike interval of the coherent spike trains. On the other hand, time-lags τ <; 1 and/or weak coupling induce negligible changes in the properties of the stochastic coherence.
Keywords
delays; neural nets; stochastic processes; white noise; attractor; coherence resonance; coherent oscillation; coherent spike train; coincident spiking; delayed coupled deterministic excitable unit; interspike interval; minimal neural network; noise induced coherence; noise value; noisy excitable system; refractory period; self-induced stochastic resonance; signal to noise ratio; signal-to-noise ratio; small noise intensity; stationary state; stochastic coherence; time delay; time-lag; white noise; Coherence; Couplings; Mathematical model; Neurons; Noise; Oscillators; Stochastic processes; Delay; Neurons; Noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Network Applications in Electrical Engineering (NEUREL), 2012 11th Symposium on
Conference_Location
Belgrade
Print_ISBN
978-1-4673-1569-2
Type
conf
DOI
10.1109/NEUREL.2012.6419957
Filename
6419957
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