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Full Description
There has been a heated debate about whether chaos theory can be applied to the dynamics of the human brain. While it is obvious that nonlinear mechanisms are crucial in neural systems, there has been strong criticism of attempts to identify at strange attractors in brain signals and to measure their fractal dimensions, Lyapunov exponents, etc. Conventional methods analyzing brain dynamics are largely based on linear models and on Fourier spectra. Regardless of the existence of strange attractors in brain activity, the neurosciences should benefit greatly from alternative methods that have been developed in recent years for the analysis of nonlinear and chaotic behavior.
Contents
Cortical dynamics - experiments and models, S. Rotter and A. Aertsen; dynamical analysis in clinical practice, P.E. Rapp and T.I. Schmah; possible clinical and research applications of nonlinear ECG analysis in humans, K. Lehnertz et al; dynamics of EEG signals during petit-mal epileptic seizures, R. Friedrich; detection of epileptic dynamics in neuromagnetic signals - spectral analyses versus characteristics of correlation function, E. Bohl et al; detection of deterministic dynamics in short discrete time series, A. Celletti et al; analysis of fluctuating data sets of diffusion processes, S. Siegert et al; analytical proof of chaos in single neurons and consequences, L. Andrey; detection of determinism in EEG time series from human sleep by an interspike interval approach, A. Galka; detection of phase synchronization in human MEG data, P. Tass et al. (Part contents)
