title: Time-frequency microstructure and statistical significance of ERD and ERS.
abstract: ERD and ERS were introduced as the time courses of the average changes of energy in given frequency bands. These curves are naturally embedded in the time-frequency plane. Time-frequency density of signals energy can be estimated by means of a variety of transforms. In general, resolution of these methods depends on a priori choices of parameters regulating the tradeoff between the time and frequency resolutions. As an exception, adaptive time-frequency approximations adapt resolution to the local structures of the analyzed signal. Matching pursuit (MP) algorithm is a reliable implementation of this approach. Its application to the event-related EEG allows for a detailed presentation of the time-frequency microstructure of changes of the average energy density, as well as calculation of high-resolution maps of ERD/ERS in the time-frequency plane. However, even with such a detailed picture of the signal energy changes, their significance remains an open issue. Owing to a stochastic character of the EEG, a visible increase or decrease of energy can occur due to a pure chance or a phenomenon unrelated to the event. For a proper estimation of the statistical significance of ERD/ERS, that is, the average changes of signals energy density in relation to the reference period, we must take into account possibly non-normal distributions of energy, and, especially, the problem of multiple comparisons appearing in hypotheses related to different frequency bands and time epochs. This chapter presents and discusses a complete framework for high-resolution estimation of the ERD/ERS microstructure in the time-frequency regions, revealing statistically significant changes.
authors.affiliation: Department of Biomedical Physics, Institute of Experimental Physics, Warsaw University, ul. Hoza 69, 00-681 Warsaw, Poland. durka@fuw.edu.pl
authors.forename: P J
authors.initials: PJ
authors.lastname: Durka
mesh_terms: D003344:Cortical Synchronization / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000706:statistics & numerical data*; D006801:Humans; D009068:Movement / Q000502:physiology; D013997:Time Factors