The dynamics of SCP when diverting from the surface of the head and when registering from the brain varies significantly and in many cases may be opposite in sign (A. Lehmenkuhler et al., 1999; etc.). For example, during abduction from the brain in animals when falling asleep, a positive shift in SCP is observed (H. Caspers, 1961), and in humans, when abducted from the surface of the head during a slow-wave sleep, a negative shift in SCP (L. Marshall et al., 1998). Therefore, the results of the above experimental work on the study of the relationship between EEG and SCP of the brain cannot be automatically transferred to humans.
Data on the correlation between changes in EEG and SCP in humans are scarce. It was shown that in patients with neurological pathology with intact EEG, the distribution of SCP is close to normal, on the contrary, the prevalence of theta and delta activities in EEG is accompanied by a significant increase in SCP (N.V. Ponomareva, 1986). Such an interrelation seems to be logical, since disturbances in energy metabolism with associated acidosis lead to the appearance of abnormal EEG activity. An increase in SCP, but less pronounced, was detected during an asynchronous type of EEG. This dependence is probably due to the fact that a high level of brain activation, manifested in the desynchronization of the EEG, requires an increased energy metabolism, and this entails acidification of the nervous tissue.
Comparison of the parameters of the EEG and the UPP of the brain helps to clarify ideas about the dynamics of UPP depending on changes in cerebral functional activity. In this paper, we studied the relationship between the parameters of the spectral power of the EEG and the UPP of the brain in healthy people, as well as in relatives of people with Alzheimer’s disease (BA) in a state of calm wakefulness and hyperventilation. The study of the correlation of EEG and SCP in these groups allows us to evaluate it with a wider range of changes in both indicators.
We examined 15 healthy subjects of both sexes (2 males and 13 females) aged from 36 to 57 years (mean age 44.7 + 1.8 years), as well as 14 clinically healthy relatives of patients with BA of the first degree of kinship (1 male and 13 women) aged 33 to 55 years (average age 45.1 + 1.6 years). Psychiatric examination was performed by N.D. Selezneva in the NCPR RAMS. All subjects to exclude cerebral pathology underwent neurological examination.
During the recording of the bioelectric activity, the subjects sat in a chair in a relaxed state with their eyes closed. EEG recording was performed on a 17-channel electroencephalograph 4317 of the company Nihon Kohden, Japan. EEG was recorded monopolarly with the location of the reference electrodes on the ear lobes, and active in 16 areas of the head in accordance with the scheme 10-20. EEG data using analog-digital the transducer was introduced into the computer for further processing. The sampling rate is 128 / s. After recording the EEG under visual control, artifacts were removed. Then carried out spectral analysis of EEG using the fast Fourier transform. Each test subject was treated with a 60-second EEG section, the era of EEG analysis was 4 seconds. The relative spectral power of the EEG was calculated for each lead and each of the frequency bands (delta 1-3.99 / c; theta 4-7.99 / c; alpha 8-12.99 / c; beta1 13-19.99 / c; beta2 20-29.99 / c). In accordance with the recommendations adopted in the EEG by T. Gasser et al. (1982) in order to obtain a normal distribution of indicators, the relative spectral power was transformed according to the formula ln [ x / (1 – x )], where x is the unconverted relative spectral power of a certain frequency range.
Due to the fact that SCP was recorded in the inferior frontal, + central and occipital regions along the sagittal line, preliminary averaged EEG parameters of the right and left hemisphere in the same regions were used for comparison between EEG and SCP. Statistical processing was carried out by methods of variation statistics. The significance of differences in the parameters of the SCP and the logarithmically transformed characteristics of the EEG in groups and under different experimental conditions was determined using univariate analysis of variance. The relationship of SCP and EEG indices was estimated using the Pearson correlation coefficient.