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
Autores principales: Rosso, O.A., Martin, M.T., Plastino, A.
Formato: JOUR
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: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 todo:paper_03784371_v320_n_p497_Rosso
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spelling todo:paper_03784371_v320_n_p497_Rosso2023-10-03T15:32:38Z Brain electrical activity analysis using wavelet-based informational tools (II): Tsallis non-extensivity and complexity measures Rosso, O.A. Martin, M.T. Plastino, A. 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. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar 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
Rosso, O.A.
Martin, M.T.
Plastino, A.
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.
format JOUR
author Rosso, O.A.
Martin, M.T.
Plastino, A.
author_facet Rosso, O.A.
Martin, M.T.
Plastino, A.
author_sort Rosso, O.A.
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
url http://hdl.handle.net/20.500.12110/paper_03784371_v320_n_p497_Rosso
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AT martinmt brainelectricalactivityanalysisusingwaveletbasedinformationaltoolsiitsallisnonextensivityandcomplexitymeasures
AT plastinoa brainelectricalactivityanalysisusingwaveletbasedinformationaltoolsiitsallisnonextensivityandcomplexitymeasures
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