ABSTRACT
A new computerized method for EEG rhythms extraction is proposed as a development of the idea of adjustable boundaries of frequency components that was put forward in previous investigations. Principle component analysis of the correlation matrix of EEG spectra with subsequent rotation of factor solutions was used for decomposition of a spectrum into physically meaningful spectral components. The method was tested on EEG of 14 healthy subjects recorded in 17 functional waking states. Fourteen independent spectral components in the spectral range from 0 to 100 Hz were extracted and their frequency boundaries were consistent with the current knowledge on frequency components of EEG oscillations. Main advantage of the described method is the adjustable estimation of EEG frequency oscillators taking into account characteristic properties of individual EEGs. Possible area of application might be the correct evaluation of spectral power of the EEG rhythms, EEG coherence and other spectral characteristics in clinical and experimental research, studies of the frequency characteristics of the EEG rhythms in different human functional states, changes in frequency characteristics of the EEG rhythms during maturation and in mental pathology.
Subject(s)
Brain Waves/physiology , Electroencephalography/methods , Principal Component Analysis , Adult , Algorithms , Female , Functional Laterality , Humans , MaleABSTRACT
Poststimulus spectral EEG changes and their correlation with evoked potential (EP) were analyzed. The non-stationary components of the brain evoked activity were revealed in 32 volunteers during simple motor reaction and choice reaction to visual stimuli. This nonstationary activity was manifested in poststimulus changes in the mean wave half-period duration (MWHPD) and mean wave half-period power of the delta- and beta-frequency oscillations computed in the EEG realizations after the EP subtraction. The latencies of high-frequency EP components fell into the intervals of the MWHPD decrease and increase in the power of beta-oscillations, and the latencies of low-frequency EP components coincided with the intervals of the MWHPD increase and decrease in the power of delta and beta-oscillations, which pointed to correlation of these changes with the EP.
