collective dynamics

Topic and aim. Synchronization in populations of coupled oscillators can be characterized with order parameters that describe collective order in ensembles. A dependence of the order parameter on the coupling constants is well-known for coupled periodic oscillators. The goal of the study is to extend this analysis to ensembles of oscillators with chaotic phases, moreover with phases possessing hyperbolic chaos. Models and methods. Two models are studied in the paper.

Aim of the paper is to review of collective dynamics study of networks of active units with pulse couplings. Many network oscillatory systems are characterized by interactions between the nodes in the form of an exchange of short signals, or pulses. The most important class of such network systems is biological neural networks, that is, populations of nerve cells. Main approaches to the study of networks with pulse coupling are described and the results obtained to date are systematized.

The aim of this review is to show the modern level of research in the area of reconstruction of network models from measured time series, for which individual nodes are described by time-delayed equations or there is a delay in coupling. Methods are described for reconstruction of coupling coefficients and functions, nonlinear functions of individual nodes and for detection of superfluous couplings. The techniques for delay time detection are considered separately due to their choice is crucial for success of entire reconstruction procedure.

Through the development of methods for detecting the dynamics of spatial-temporal patterns of activity in the nervous system fundamental evidences obtained, that the sensory code have integrative nature and theories of localisation of function are inconsistent. The paper presents a review of electrophysiological data and models, indicating the integrative mechanisms of information coding in the peripheral skin analyzer of humans and animals.