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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Physica A: Statistical Mechanics and its Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
