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Comparative Study
. 1984;6(3):289-303.
doi: 10.1016/s0387-7604(84)80042-x.

Ontogenic development of autoregressive component waves of waking EEG in normal infants and children

Comparative Study

Ontogenic development of autoregressive component waves of waking EEG in normal infants and children

T Ogawa et al. Brain Dev. 1984.

Abstract

Waking EEGs of 150 normal children aged from 20 days to 15 years were subjected to analysis. Discrete time series of an artifact free segment of the EEG record at 50 samples/sec for twenty seconds was generated and autoregressive (AR) and component analyses were carried out with a minicomputer PDP 11/40 (DEC). The results may be summarized as follows: 1) In the group of 1 year old and less, the power increased with the monthly age, whereas the bio-informing activity amount decreased. In those older than 1 year, both parameters showed maximal values at 1 year and then decreased with age, and the decreases were marked from 1 to 3 years. 2) The first- and second-order component activities of 129 and 677 waves, respectively, were obtained by applying component analysis to 152 EEG records. The frequency polygons of natural frequency of second-order component waves verified several modes, each of which was enhanced in the frequency range of the well-known delta 0, delta 1, theta 1, theta 2, alpha 1, alpha 2, beta 1, beta 2 and beta 3 waves, respectively. 3) The average percent-power of the delta wave (delta 0 + delta 1) decreased with age, especially from 1 to 3 years old, whereas those of beta- and alpha-waves increased with advancing age. That of the theta wave tended to increase from 2 to 4 years of age, and thereafter decreased gradually with increasing age. 4) With increasing age, the durations of damped oscillations were significantly lengthened in delta 1, alpha 1 and beta 3 waves, whereas that in the theta 1 wave was significantly shortened. 5) The bio-informing activity amounts of alpha waves increased from 1 to 3 years with increasing age, whereas those of delta and theta waves decreased. No significant developmental change in the parameters, however, was observed in the beta wave. The results indicate that AR-power spectral and component analyses of EEG are sensitive methods for obtaining valuable information regarding the electrical brain maturation in childhood.

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