title: EEG analysis using wavelet-based information tools.
abstract: Wavelet-based informational tools for quantitative electroencephalogram (EEG) record analysis are reviewed. Relative wavelet energies, wavelet entropies and wavelet statistical complexities are used in the characterization of scalp EEG records corresponding to secondary generalized tonic-clonic epileptic seizures. In particular, we show that the epileptic recruitment rhythm observed during seizure development is well described in terms of the relative wavelet energies. In addition, during the concomitant time-period the entropy diminishes while complexity grows. This is construed as evidence supporting the conjecture that an epileptic focus, for this kind of seizures, triggers a self-organized brain state characterized by both order and maximal complexity.
authors: Chaos and Biology Group, Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires. Pabellón II, Ciudad Universitaria, 1428 Ciudad de Buenos Aires, Argentina. oarosso@fibertel.com.ar
authors: O A
authors: OA
authors: Rosso
authors: M T
authors: MT
authors: Martin
authors: A
authors: A
authors: Figliola
authors: K
authors: K
authors: Keller
authors: A
authors: A
authors: Plastino