Stochastic model and synchronization analysis for large-scale oscillator networks and their applications

Networks of coupled large-scale oscillators have been studied in biology for a number of years. It has been recognized that transients in the nearest neighbour connected networks may take far too long to die out. It is considered that a few long-distance interconnections exist. Typically, these long-distance interconnections are considered to occur in a random way. In this paper, the synchronization problem for coupled oscillator networks is discussed. Then, the stochastic distribution model for the random long-distance connections is proposed and the validity is demonstrated by simulation. Furthermore, the proposed oscillator network is applied to the visual model of a dragonfly.

[1]  Masatoshi Sekine,et al.  Synchronized Firings in the Networks of Class 1 Excitable Neurons with Excitatory and Inhibitory Connections and Their Dependences on the Forms of Interactions , 2005, Neural Computation.

[2]  Xiao Fan Wang,et al.  Synchronization in Small-World Dynamical Networks , 2002, Int. J. Bifurc. Chaos.

[3]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[4]  Paul H. E. Tiesinga Stimulus competition by inhibitory interference , 2006, Neurocomputing.

[5]  L. Chua,et al.  Synchronization in an array of linearly coupled dynamical systems , 1995 .

[6]  D. Watts,et al.  Small Worlds: The Dynamics of Networks between Order and Randomness , 2001 .

[7]  Michael N. Shadlen,et al.  Synchrony Unbound A Critical Evaluation of the Temporal Binding Hypothesis , 1999, Neuron.

[8]  J. Hasty,et al.  Synchronizing genetic relaxation oscillators by intercell signaling , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Guanrong Chen,et al.  Synchronization and desynchronization of complex dynamical networks: an engineering viewpoint , 2003 .

[10]  Hilbert J. Kappen,et al.  Input-Driven Oscillations in Networks with Excitatory and Inhibitory Neurons with Dynamic Synapses , 2007, Neural Computation.

[11]  Corey D. Acker,et al.  Synchronization in hybrid neuronal networks of the hippocampal formation. , 2005, Journal of neurophysiology.

[12]  Nancy Kopell,et al.  Effects of Noisy Drive on Rhythms in Networks of Excitatory and Inhibitory Neurons , 2005, Neural Computation.

[13]  W. P. Dayawansa,et al.  Phase locking in the mammalian circadian clock , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[14]  J. D. Miller,et al.  New insights into the mammalian circadian clock. , 1996, Sleep.

[15]  F. Verhulst Nonlinear Differential Equations and Dynamical Systems , 1989 .

[16]  Richard Bellman,et al.  Introduction to Matrix Analysis , 1972 .

[17]  N. Kopell We Got Rhythm: Dynamical Systems of the Nervous System , 1999 .

[18]  C A Czeisler,et al.  Mathematical model of the human circadian system with two interacting oscillators. , 1982, The American journal of physiology.

[19]  Nancy Kopell,et al.  Synchronization in Networks of Excitatory and Inhibitory Neurons with Sparse, Random Connectivity , 2003, Neural Computation.

[20]  John Rinzel,et al.  Synchronization of Electrically Coupled Pairs of Inhibitory Interneurons in Neocortex , 2007, The Journal of Neuroscience.

[21]  Nicolas Brunel,et al.  Contributions of intrinsic membrane dynamics to fast network oscillations with irregular neuronal discharges. , 2005, Journal of neurophysiology.

[22]  Christof Cebulla,et al.  Asymptotic Behavior and Synchronizability Characteristics of a Class of Recurrent Neural Networks , 2007, Neural Computation.