The EEG consists of the activity of an ensemble of generators producing rhy
thmic activity in several frequency ranges. These oscillators are active us
ually in a random way. However, by application of sensory stimulation these
generators are coupled and act together in a coherent way. This synchroniz
ation and enhancement of EEG activity gives rise to 'evoked' or 'event-rela
ted oscillations'. The compound evoked potential manifests as superimpositi
on of evoked rhythms in the EEG frequencies ranging from delta tio gamma ('
natural frequencies of the brain'). The superimposition principle is descri
bed with efficient strategies and by utilization of an efficient algorithm.
The wavelet analysis confirms the results of the combined analysis procedu
re obtained by using the amplitude frequency characteristics (AFCs) and dig
ital filtering. The AFC and adapted digital filtering methods are based on
the first approach to analyze average evoked potentials. In contrast, the w
avelet analysis is based on signal retrieval and selection among a large nu
mber of sweeps recorded in a given physiological or psychological experimen
t. By combining all these results and concepts, it can be stated that the w
avelet 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 anal
ysis confirms once more the expression 'real signals' which we attribute to
EEG frequency responses of the brain. It will be demonstrated that the del
ta, theta, and alpha responses (i.e. the rhythms 'predicted' by digital fil
tering) are real brain oscillations. The frequency components of the event-
related potential vary independently of each other with respect to: (a) the
ir relation to the event; (b) their topographic distribution; and (c) with
the mode of the physiological measurements. (C) 2001 Elsevier Science B.V.
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