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

O.a Rosso, M.t Martin and A Plastino

Physica A: Statistical Mechanics and its Applications, 2003, vol. 320, issue C, 497-511

Abstract: 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.

Keywords: EEG; Epileptic seizures; Time–frequency signal analysis; Wavelet analysis; Signal entropy; Complexity (search for similar items in EconPapers)
Date: 2003
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:320:y:2003:i:c:p:497-511

DOI: 10.1016/S0378-4371(02)01529-7

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