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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 electroencephalograph desynchronization and synchronization (ERD/ERS) in the time-frequency plane.

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