title: Event-related oscillations are 'real brain responses'--wavelet analysis and new strategies.
abstract: The EEG consists of the activity of an ensemble of generators producing rhythmic activity in several frequency ranges. These oscillators are active usually in a random way. However, by application of sensory stimulation these generators are coupled and act together in a coherent way. This synchronization and enhancement of EEG activity gives rise to 'evoked' or 'event-related oscillations'. The compound evoked potential manifests as superimposition of evoked rhythms in the EEG frequencies ranging from delta to gamma ('natural frequencies of the brain'). The superimposition principle is described with efficient strategies and by utilization of an efficient algorithm. The wavelet analysis confirms the results of the combined analysis procedure obtained by using the amplitude frequency characteristics (AFCs) and digital filtering. The AFC and adapted digital filtering methods are based on the first approach to analyze average evoked potentials. In contrast, the wavelet analysis is based on signal retrieval and selection among a large number of sweeps recorded in a given physiological or psychological experiment. By combining all these results and concepts, it can be stated that the wavelet analysis underlines and extends the expression that alpha-, theta-, delta-, and gamma-responses described in this report are the most important brain responses related to psychophysiological functions. The wavelet analysis confirms once more the expression 'real signals' which we attribute to EEG frequency responses of the brain. It will be demonstrated that the delta, theta, and alpha responses (i.e. the rhythms 'predicted' by digital filtering) are real brain oscillations. The frequency components of the event-related potential vary independently of each other with respect to: (a) their relation to the event; (b) their topographic distribution; and (c) with the mode of the physiological measurements.
authors.affiliation: Institute of Physiology, Medical University Lubeck, Ratzeburger Allee 160, 23538, Lubeck, Germany. erol.basar@deu.edu.tr
authors.forename: E
authors.initials: E
authors.lastname: Başar
authors.forename: M
authors.initials: M
authors.lastname: Schürmann
authors.forename: T
authors.initials: T
authors.lastname: Demiralp
authors.forename: C
authors.initials: C
authors.lastname: Başar-Eroglu
authors.forename: A
authors.initials: A
authors.lastname: Ademoglu
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000502:physiology*; D004569:Electroencephalography / Q000379:methods* / Q000706:statistics & numerical data; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans