Features of the Electrical Cortical Signal in Steady State and in White Flash Stimulation

The features of the electrical cortical signals are described in terms of relative power and variation coefficient extracted from the analysis of both steady state and white flash visual stimulation. Different frequency ranges of brain activity, common for visual processing, are considered. An EEG analyzer Zwonitz 2000 and a system of 19 silver electrodes situated on specific scalp areas, with ear reference, were used for the recordings. The stimulation was done by white flashes from a distance of approximately 30 cm in front of the eyes, in 30 normal subjects. Amplitudes and frequency of the signals from monopolar recording were estimated. The method Quellen Ableitung (QA) or source derivation was applied. This method mostly eliminates the surface currents and helps recording only the vertical electric currents, which appear from the nerve cells discharges on the normal direction on the scalp surface.Using the average values obtained, we have mapped the values in different domains of frequencies on different areas on the scalp both in steady state and flash stimulation. The EEG recorder Bioscript 2000 - Zwonitz with dedicated programs for the QA method helped to perform the numerical signal analysis. Spectral power values relative to each frequency domain at rest (steady state) and at white flash stimulation were obtained for each subject. Collected EEG data were further visualized on a computer monitor for manual artifacts removal. Artifact free 40-second sequences were selected. The data was digitally processed using a Fast Fourier Transform algorithm, with windows set for the important frequency bands: Delta-2 (1.95-3.91) Hz, Theta (3.91- 7.81) Hz, Alpha (7.81-12.78) Hz and Beta (12.78-25.88) Hz. The values for each recording location were then mapped.We conclude that the brain is optimally processing visual signals with patterns of inhomogeneous distribution of specific features described in this work. Some clinical dysfunctions of the occipital visual areas could be detected from the signal analysis presented here. In the same time, the procedure is adequate for the evaluation when the development of specific pathologies is monitored.