Spatio-temporal dynamics of human EEG

Autor: I. David, Ivan Dvořák, Milan Paluš
Rok vydání: 1992
Předmět:
Zdroj: Physica A: Statistical Mechanics and its Applications. 185:433-438
ISSN: 0378-4371
DOI: 10.1016/0378-4371(92)90485-9
Popis: Electroencephalogram (EEG)- recording of spontaneous brain electrical activity resulting from collective dynamical behaviour of the neural mass - was traditionally treated as a random signal and processed by stochastic methods like spectral analysis. Qualitatively new views were opened by approaches derived from synergetics, non-linear dynamics and theory of deterministic chaos introduced into EEG research in the last six years (see refs. [1, 2], and references therein). In this approach the EEG signal is supposed to be a deterministic signal generated by chaotic dynamics of finite and even low- dimensional dynamical system evolving on its strange attractor. Processing EEG data consists then of the reconstruction of a hypothetical strange attractor from experimental data and computations of relevant dynamical/topological invariants (fractal dimensions, Lyapunov exponents, Kolmogorov entropy). The goal of this treatment is using measures of complexity and chaos for characterization of brain processes reflected in the EEG signal, i.e. developing new tools for computerized EEG analysis with applications in psychiatry, neurology and pharmacology of psychoactive drugs. EEG signals can be simultaneously registered from several locations on the scalp (16, 32, 64). Two ways of reconstructing the "brain attractor" are presently used: One-channel reconstruction. A one-dimensional ("one-channel") EEG signal registered from a particular location on the scalp is considered as a smooth projection of n-dimensional chaotic dynamics on the strange attractor. An n-dimensional trajectory is reconstructed using the time-delay method based Affiliated to 3rd School of Medicine, Charles University Prague; e-mail: pcpmp@csearn.bitnet. 0378-4371/92/$05.00 (~) 1992- Elsevier Science Publishers B.V. All rights reserved
Databáze: OpenAIRE
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