On the statistical significance of event-related EEG desynchronization and synchronization in the time-frequency plane

Piotr J. Durka, Jarosaw Zygierewicz, Hubert Klekowicz, Józef Ginter, Katarzyna J. Blinowska

IEEE Transactions on Biomedical Engineering, 2003. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Download: article PDF file (2 column) PDF file (1 column),
software for calculating t-f statistics in Matlab,
software --"-- + datasets used in this study.
README file coming with the software.

Abstract:

We propose and discuss a complete framework for estimating significant changes in the average time-frequency density of energy of event-related signals. Addressed issues include estimation of time-frequency energy density (matching pursuit and spectrogram), choice of resampling statistics to test the hypothesis of change in one small region (resel) and correction for multiplicity (False Discovery Rate). We present estimation of the significance of event-related EEG desynchronization and synchronization (ERD/ERS) in the time-frequency plane.

Complete software implementing all the discussed steps is freely available from the Internet at
http://durka.info/tfstat.