SENSING INTERACTION DYNAMICS OF CHAOTIC SYSTEMS WITHIN A CHAOS THEORY AND MICROSYSTEM TECHNOLOGY GEOMATH WITH APPLICATION TO NEUROPHYSIOLOGICAL SYSTEMS

Abstract

Paper is devoted to studying dynamics of the nonlinear neuro-physiological systems identifying the presence of chaotic elements. The mutual information approach, correlation integral analysis, false nearest neighbour algorithm, Lyapunov exponent's analysis, and surrogate data method are used for comprehensive characterization on the basis of Geomath microsystem technology. The correlation dimension method provided a low fractal-dimensional attractor thus suggesting a possibility of the existence of chaotic behavior. Statistical significance of the results was confirmed by testing for a surrogate data. We also present the concrete numerical results regarding the ensembles fluctuations of spontaneous Parkinsonian tremor and fluctuations of the local potential.