Brain electrical activity analysis using wavelet-based informational tools (II): Tsallis non-extensivity and complexity measures

The processing of information by the brain is reflected in dynamical changes of the electrical activity in (i) time, (ii) frequency, and (iii) space. Therefore, the concomitant studies require methods capable of describing the qualitative variation of the signal in both time and frequency. The prese...

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Detalles Bibliográficos
Publicado: 2003
Materias:
Complexity
Epileptic seizures
Signal entropy
Time-frequency signal analysis
Wavelet analysis
Brain
Information theory
Neurology
Signal processing
Wavelet transforms
Signal analysis
Electroencephalography
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v320_n_p497_Rosso
http://hdl.handle.net/20.500.12110/paper_03784371_v320_n_p497_Rosso
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_03784371_v320_n_p497_Rosso
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spelling paper:paper_03784371_v320_n_p497_Rosso2023-06-08T15:39:58Z Brain electrical activity analysis using wavelet-based informational tools (II): Tsallis non-extensivity and complexity measures Complexity Epileptic seizures Signal entropy Time-frequency signal analysis Wavelet analysis Brain Information theory Neurology Signal processing Wavelet transforms Signal analysis Electroencephalography The processing of information by the brain is reflected in dynamical changes of the electrical activity in (i) time, (ii) frequency, and (iii) space. Therefore, the concomitant studies require methods capable of describing the qualitative variation of the signal in both time and frequency. The present work complements the efforts described in Rosso et al. (Physica A 313 (2002) 587), devoted to non-extensive information measures à la Tsallis. Here we show that the notion of complexity, using (1) appropriate information-theory tools (adapted to a non-extensive scenario) and (2) scalp EEG data, provides one with valuable insights into the dynamics of neural activity. In particular, using different complexity measures we detect the presence of states characterized by both order and maximal complexity. © 2002 Elsevier Science B.V. All rights reserved. 2003 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v320_n_p497_Rosso http://hdl.handle.net/20.500.12110/paper_03784371_v320_n_p497_Rosso
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Complexity
Epileptic seizures
Signal entropy
Time-frequency signal analysis
Wavelet analysis
Brain
Information theory
Neurology
Signal processing
Wavelet transforms
Signal analysis
Electroencephalography
spellingShingle Complexity
Epileptic seizures
Signal entropy
Time-frequency signal analysis
Wavelet analysis
Brain
Information theory
Neurology
Signal processing
Wavelet transforms
Signal analysis
Electroencephalography
Brain electrical activity analysis using wavelet-based informational tools (II): Tsallis non-extensivity and complexity measures
topic_facet Complexity
Epileptic seizures
Signal entropy
Time-frequency signal analysis
Wavelet analysis
Brain
Information theory
Neurology
Signal processing
Wavelet transforms
Signal analysis
Electroencephalography
description The processing of information by the brain is reflected in dynamical changes of the electrical activity in (i) time, (ii) frequency, and (iii) space. Therefore, the concomitant studies require methods capable of describing the qualitative variation of the signal in both time and frequency. The present work complements the efforts described in Rosso et al. (Physica A 313 (2002) 587), devoted to non-extensive information measures à la Tsallis. Here we show that the notion of complexity, using (1) appropriate information-theory tools (adapted to a non-extensive scenario) and (2) scalp EEG data, provides one with valuable insights into the dynamics of neural activity. In particular, using different complexity measures we detect the presence of states characterized by both order and maximal complexity. © 2002 Elsevier Science B.V. All rights reserved.
title Brain electrical activity analysis using wavelet-based informational tools (II): Tsallis non-extensivity and complexity measures
title_short Brain electrical activity analysis using wavelet-based informational tools (II): Tsallis non-extensivity and complexity measures
title_full Brain electrical activity analysis using wavelet-based informational tools (II): Tsallis non-extensivity and complexity measures
title_fullStr Brain electrical activity analysis using wavelet-based informational tools (II): Tsallis non-extensivity and complexity measures
title_full_unstemmed Brain electrical activity analysis using wavelet-based informational tools (II): Tsallis non-extensivity and complexity measures
title_sort brain electrical activity analysis using wavelet-based informational tools (ii): tsallis non-extensivity and complexity measures
publishDate 2003
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v320_n_p497_Rosso
http://hdl.handle.net/20.500.12110/paper_03784371_v320_n_p497_Rosso
_version_ 1768542318598553600

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