| Abstrakt: |
Since Berger's discovery of the electroencephalogram (EEG), its analysis has been generally restricted to the visual range (upmost 100Hz) and has ignored higher frequency components. One reason should be that there are no reliable methods to distinguish the brain potentials from muscle activity. We have introduced fluctuation analysis, which is popular method especially in the field of basic physiology to clinical electrophysiology. In our previous study, it was declared that power spectral density (PSD) of human high frequency EEG was composed of double Lorentzians and vanished into white level within 1kHz. Then the purpose of this study is to elucidate the "Automated Fluctuation Analysis," which enables us to evaluate these higher frequency components and its physiological meaning especially focused on conscious level from wakefulness to sleep stage 1. Seventy-four scalp recording EEGs in twenty normal subjects were studied. In short, "Automated Fluctuation Analysis" is made of three steps: amplification of EEG signal, A/D conversion and Fast Fourier Transform by signal processor and extraction of Lorentzian parameters. PSD of high frequency EEG was displayed on log-log graph and the algorithm fit to the following Lorentzian formula were mathematically based on Brown & Dennis. S(f) = S1/[1+(f/fc1)2]+S2/[1+(f/fc2)2], where S(f) is PSD (mu V2/Hz) at each frequency (f;Hz), S1 and S2 are the plateau level or zero-frequency power of the initial and second Lorentz, and fc1 and fc2 are the corner or half-power frequency of the initial and second Lorentz, respectively. As results, during wakefulness the PSD of high frequency EEG activity was composed of double Lorentzian fluctuations and the power distribution of S1 value in topographical display was frontal dominant. This pattern of S1 value disappeared and S2 value became lower during sleepiness and the second Lorentz disappeared during sleep. |
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