Search

In this paper we study the relaxation singularities of human motor system at aging. Our purpose is to examine the structure of force output variability as a function of human aging in the time and frequency domains. For analysis of experimental data we have developed here the statistical theory of relaxation of force output fluctuation with taking into account the effects of two relaxation channels. The first of them contains the contribution of short-range correlation whereas other relaxation component reflects the effect of long-range correlation. The analysis of experimental data shows, that the general behavior of relaxation processes at human aging is determined by a complicated combination and nonlinear interactions two above stated relaxation processes as a whole., Comment: 28 pages, 18 figures, Submitted to Nonlinear Phenomena in Complex Systems, Minsk, Belarus

Dynamical wiring and rewiring in neural networks are carried out by activity-dependent growth and retraction of axons and dendrites, guided by gudance molecules, released by target cells. Experience-dependent structural changes in cortical microcurcuts lead to changes in activity, i.e. to changes in information encoded. Specific pattens of external stimulation can lead to creation of new synaptical connections between neurons. Calcium influxes controlled by neuronal activity regulates processes of neurotrophic factors release by neurons, growth cones movement and synapse differentiation in developing neural system, therefore activity-dependent self-wiring can serve as a basis of structural plasticity in cortical networks and can be considered as a form of learning., Comment: 5 pages, 3 figures

We propose a model for description of activity-dependent evolution and self-wiring between binary neurons. Specifically, this model can be used for investigation of growth of neuronal connectivity in the developing neocortex. By using computational simulations with appropriate training pattern sequences, we show that long-term memory can be encoded in neuronal connectivity and that the external stimulations form part of the functioning neocortical circuit. It is proposed that such binary neuron representations of point-like cortical neurons fail to reproduce cytoarchitectural differences of the neocortical organization, which has implications for inadequacies of compartmental models., Comment: 13 pages, 5 figures

In this work we develop a new method of diagnosing the nervous system diseases and a new approach in studying human gait dynamics with the help of the theory of discrete non-Markov random processes. The stratification of the phase clouds and the statistical non-Markov effects in the time series of the dynamics of human gait are considered. We carried out the comparative analysis of the data of four age groups of healthy people: children (from 3 to 10 year olds), teenagers (from 11 to 14 year oulds), young people (from 21 up to 29 year oulds), elderly persons (from 71 to 77 year olds) and Parkinson patients. The full data set are analyzed with the help of the phase portraits of the four dynamic variables, the power spectra of the initial time correlation function and the memory functions of junior orders, the three first points in the spectra of the statistical non-Markov parameter. The received results allow to define the predisposition of the probationers to deflections in the central nervous system caused by Parkinson's disease. We have found out distinct differencies between the five submitted groups. On this basis we offer a new method of diagnostics and forecasting Parkinson's disease., Comment: 15 pages, 5 figs, 3 Tables

The study of social networks and especially of the stochastic dynamics of the diseases spread in human population has recently attracted considerable attention in statistical physics. In this work we present a new statistical method of analyzing the spread of epidemic processes of grippe and acute respiratory track infections (ARTI) by means of the theory of discrete non-Markov stochastic processes. We use the results of our last theory (Phys. Rev. E 65, 046107 (2002)) to study statistical memory effects, long - range correlation and discreteness in real data series, describing the epidemic dynamics of human ARTI infections and grippe. We have carried out the comparative analysis of the data of the two infections (grippe and ARTI) in one of the industrial districts of Kazan, one of the largest cities of Russia. The experimental data are analyzed by the power spectra of the initial time correlation function and the memory functions of junior orders, the phase portraits of the four first dynamic variables, the three first points of the statistical non-Markov parameter and the locally averaged kinetic and relaxation parameters. The received results give an opportunity to provide strict quantitative description of the regular and stochastic components in epidemic dynamics of social networks taking into account their time discreteness and effects of statistical memory. They also allow to reveal the degree of randomness and predictability of the real epidemic process in the specific social network., Comment: 18 pages, 8figs, 1 tables

The basic purpose of the paper is to draw the attention of researchers to new possibilities of differentiation of similar signals having different nature. One of examples of such kind of signals is presented by seismograms containing recordings of earthquakes (EQ's) and technogenic explosions (TE's). We propose here a discrete stochastic model for possible solution of a problem of strong EQ's forecasting and differentiation of TE's from the weak EQ's. Theoretical analysis is performed by two independent methods: with the use of statistical theory of discrete non-Markov stochastic processes (Phys. Rev. E62,6178 (2000)) and the local Hurst exponent. Time recordings of seismic signals of the first four dynamic orthogonal collective variables, six various plane of phase portrait of four dimensional phase space of orthogonal variables and the local Hurst exponent have been calculated for the dynamic analysis of the earth states. The approaches, permitting to obtain an algorithm of strong EQ's forecasting and to differentiate TE's from weak EQ's, have been developed., Comment: REVTEX +12 ps and jpg figures. Accepted for publication in Phys. Rev. E, December 2001

In this paper we present the concept of description of random processes in complex systems with the discrete time. It involves the description of kinetics of discrete processes by means of the chain of finite-difference non-Markov equations for time correlation functions (TCF). We have introduced the dynamic (time dependent) information Shannon entropy $S_i(t)$ where i=0,1,2,3,... as an information measure of stochastic dynamics of time correlation $(i=0)$ and time memory (i=1,2,3,...). The set of functions $S_i(t)$ constitute the quantitative measure of time correlation disorder $(i=0)$ and time memory disorder (i=1,2,3,...) in complex system. Harnessing the infinite set of orthogonal dynamic random variables on a basis of Gram-Shmidt orthogonalization procedure tends to creation of infinite chain of finite-difference non-Markov kinetic equations for discrete TCF and memory function.The solution of the equations above thereof brings to the recurrence relations between the TCF and MF of senior and junior orders. The results obtained offer considerable scope for attack on stochastic dynamics of discrete random processes in a complex systems. Application of this technique on the analysis of stochastic dynamics of RR-intervals from human ECG's shows convincing evidence for a non-Markovian phenomemena associated with a peculiarities in short and long-range scaling. This method may be of use in distinguishing healthy from pathologic data sets based in differences in these non-Markovian properties., Comment: 20 pages, RevTeX, 1 table, 2 eps figures