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New information technologies in the analysis of electroencephalograms

Today, the evidence of the Eskov–Zinchenko effect is becoming increasingly widespread. In this case, it is proved that any set of human body parameters is unique (statistically unique). Now we are also applying this effect to the neural networks of the brain. An analysis of electroencephalograms shows that brain biopotentials are not statistically stable. For the electroencephalograms analysis, it is proposed to create paired sample comparison matrices and find numbers k of the sample pairs that can have one (common) general population. It was found that these numbers k depend on the physiological state of the test subject. For example, for epileptic patients, number k increases dramatically, and it usually does not exceed 30-45% of all 105 pairs in each of such paired comparison matrices.