Open AccessThe search for statistical patterns of pathological activity in human EEG signals in focal epilepsy
Author(s) -
Valentin Yunusov,
Sergey Demin,
O. Yu. Panischev,
Natalya Demina
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2103/1/012044
Subject(s) - epilepsy , temporal lobe , electroencephalography , statistical analysis , neuroscience , pathological , computer science , psychology , artificial intelligence , pattern recognition (psychology) , medicine , pathology , mathematics , statistics
Modern data science faces a lot of challenges, one of which is the search for diagnostic criteria for neurological diseases. New methods of statistical analysis are actively applied in the field of biophysics to solve this issue. In this paper we apply the Memory Functions Formalism to analyze electroencephalogram signal recordings in the sleeping state of 8 healthy subjects and 19 patients with nocturnal lobe epilepsy. We observe the considerable difference of statistical memory effects and fractal properties at the pathology in comparison with the control group. Furthermore, we reveal significant alterations in brain rhythms at power spectra of statistical memory functions for two groups of subjects. As a result, we show that the application of the statistical analysis methodology of bioelectrical brain cortex activity recordings, after appropriate verification, can be useful in the search for diagnostic criteria of nocturnal frontal lobe epilepsy.