• Speaker: Joe Lakey, New Mexico State University
  • Title: Some Mathematical Tools for Analysis of EEG data
  • Location: Room V205, Mathematics Building (Callaghan Campus) The University of Newcastle
  • Time and Date: 4:00 pm, Thu, 11th Jun 2015
  • Abstract:

    Advantages of EEG in studying brain signals include excellent temporal localization and, potentially, good spatial localization, given good models for source localization in the brain. Phase synchrony and cross-frequency coupling are two phenomena believed to indicate cooperation of different brain regions in cognition through messaging via different frequency bands. To verify these hypotheses requires ability to extract time-frequency localized components from complex multicomponent EEG data. One such method, empirical mode decompositions, shows increasing promise through engineering and we will review recent progress on this approach. Another potential method uses bases or frames of optimally time-frequency localized signals, so-called prolate spheroidal wave functions. New properties of these functions developed in joint work with Jeff Hogan will be reviewed and potential applications to EEG will be discussed.

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