Dynamic spectral analysis of event-related EEG data.
A method for analysing the time course of power spectra of event-related EEG data is presented. A sequence of autoregressive models is fitted to segments of the EEG within which the data exhibit local stationarity. For parameter estimation a method involving ensemble averages is introduced. Besides investigating the evolution of power spectra, time courses of peak frequency, bandwidth and power of alpha (mu) and beta rhythms are traced. The method is applied to EEG recorded over the primary motor area during self-paced finger movements.
D004569:Electroencephalography / Q000706:statistics & numerical data*; D005071:Evoked Potentials / Q000502:physiology*; D008433:Mathematics; D015233:Models, Statistical; D013997:Time Factors