The robustness and breakup of spiral wave in a two-dimensional lattice networks of neurons are investigated. The effect of small- world type connection is often simplified with local regular connection and the long-range connection with certain probability. The network effect on the development of spiral wave can be better described by local regular connection and changeable long-range connection probability than fixed long-range connection probability because the long-range probability could be changeable in realistic biological system. The effect from the changeable probability for long-range connection is simplified by multiplicative noise. At first, a stable rotating spiral wave is developed by using appropriate initial values, parameters and no-flux boundary conditions, and then the effect of networks is investigated. Extensive numerical studies show that spiral wave keeps its alive and robust when the intensity of multiplicative noise is below a certain threshold, otherwise, the breakup of spiral wave occurs. A statistical factor of synchronization in two-dimensional array is defined to study the phase transition of spiral wave by checking the membrane potentials of all neurons corresponding to the critical parameters(the intensity of noise or forcing current)in the curve for factor of synchronization. The Hindmarsh-Rose model is investigated, the Hodgkin-Huxley neuron model in the presence of the channel noise is also studied to check the model independence of our conclusions. And it is found that breakup of spiral wave is easier to be induced by the multiplicative noise in presence of channel noise.
MA Jun 1,2, TANG Jun 2 , ZHANG AiHua 3 & JIA Ya 2 1 Department of Physics, Lanzhou University of Technology, Lanzhou 730050, China
In this paper, the synchronization and the parameter identification of the chaotic Pikovsky-Rabinovich （PR） circuits are investigated. The linear error of the second corresponding variables is used to change the driven chaotic PR circuit, and the complete synchronization of the two identical chaotic PR circuits is realized with feedback intensity k increasing to a certain threshold. The Lyapunov exponents of the chaotic PR circuits are calculated by using different feedback intensities and our results are confirmed. The case where the two chaotic PR circuits are not identical is also investigated. A general positive Lyapunov function V, which consists of all the errors of the corresponding variables and parameters and changeable gain coefficient, is constructed by using the Lyapunov stability theory to study the parameter identification and complete synchronization of two nomidentical chaotic circuits. The controllers and the parameter observers could be obtained analytically only by simplifying the criterion dV/dt 〈 0 （differential coefficient of Lyapunov function V with respect to time is negative）. It is confirmed that the two non-identical chaotic PR circuits could still reach complete synchronization and all the unknown parameters in the drive system are estimated exactly within a short transient period.
The effect of change in concentration of messenger molecule inositol 1,4,5-trisphosphate （IP3） on intracellular Ca^2＋spiral pattern evolution is studied numerically. The results indicate that when the IP3 concentration decreases from 0.27 μM, a physiologically reasonable value, to different values, the spiral centre drifts to the edge of the medium and disappears for a small enough IP3 concentration. The instability of spiral pattern can be understood in terms of excitability-change controlled by the IP3 concentration. On the other hand, when the IP3 concentration increases from 0.27 μM, a homogeneous area with a high Ca^2＋ concentration emerges and competes with the spiral pattern. A high enough IP3 concentration can lead the homogeneous area to occupy the whole medium. The instability of spiral pattern is ascribed to the change in stability of a stationary state with a high Ca^2＋ concentration.
This paper proposes a scheme of parameter perturbation to suppress the stable rotating spiral wave, meandering spiral wave and turbulence in the excitable media, which is described by the modified Fitzhug-Nagumo （MFHN） model. The controllable parameter in the MFHN model is perturbed with a weak pulse and the pulse period is decided by the rotating period of the spiral wave approximatively. It is confirmed that the spiral wave and spiral turbulence can be suppressed greatly. Drift and instability of spiral wave can be observed in the numerical simulation tests before the whole media become homogeneous finally.
The phase transition of spiral waves in networks of Hodgkin-Huxley neurons induced by channel noise is investigated in detail.All neurons in the networks are coupled with small-world connections,and the results are compared with the case for regular networks,in which all neurons are completely coupled with nearest-neighbor connections.A statistical variable is defined to study the collective behavior and phase transition of the spiral wave due to the channel noise and topology of the network.The effect of small-world connection networks is described by local regular networks and long-range connection with certain probability p.The numerical results confirm that (1) a stable rotating spiral wave can be developed and maintain robust with low p,where the breakup of the spiral wave and turbulence result from increasing the probability p to a certain threshold;(2) appropriate intensity of the optimized channel noise can develop a spiral wave among turbulent states in small-world connection networks of H-H neurons;and (3) regular connection networks are more robust to channel noise than small-world connection networks.A spiral wave in a small-world network encounters instability more easily as the membrane temperature is increased to a certain high threshold.
