Estimating the relative phase-difference in EEG using the matched phase reassigned cross-spectrogram

Sammanfattning: In brain connectivity research the relative phase between two EEG oscillations is particularly relevant, as it could provide information about the conduction delay between two regions. However, due to EEG signals containing large amounts of noise and spurious connections, the relative phase is seldom estimated. The aim of this thesis is to explore the possibilities of estimating relative phase using an algorithm based of the scaled reassigned spectrogram (ScRe-Spec) and the matched phase reassignment (MPR). Through simulations it is shown that both the Rényi entropy and the time-frequency concentration are suitable methods for evaluating the reassigned spectrograms. The algorithm is shown to give more correct estimations in comparison to other relative-phase estimation methods when the signal to noise ratio is low. Lastly, when tested on two real EEG-data examples, the algorithm shows promising results.