ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)


For citation:

Grishchenko A. A., Sysoeva M. V., Sysoev I. V. Detecting the primary time scale of evolution of information properties for local field potentials in brain at absence epilepsy. Izvestiya VUZ. Applied Nonlinear Dynamics, 2020, vol. 28, iss. 1, pp. 98-110. DOI: 10.18500/0869-6632-2020-28-1-98-110

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
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Russian
Article type: 
Article
UDC: 
530.182, 51-73

Detecting the primary time scale of evolution of information properties for local field potentials in brain at absence epilepsy

Autors: 
Grishchenko A. A., Saratov State University
Sysoeva Marina Vyacheslavovna, Yuri Gagarin State Technical University of Saratov
Sysoev Ilya V., Saratov State University
Abstract: 

The purpose of the current study is to determine how the characteristic time (lag) responsible for keeping information about the previous dynamics in the brain local field potential signals evaluates in time. This time is necessary to know in order to construct forecasting models for coupling estimation and seizure prediction and detection. Methods. Mutual information function calculated between a signal with itself shifted in time is used. The shift varies from 0 to one half of characteristic oscillation period. Mann–Whitney test is used for comparative statistical analysis of distributions of the lag obtained for different animals and recordings. Results. Two records of local field potentials for each of five WAG/Rij rats (genetic models of absence seizures) were analyzed. Four channels were taken into account: frontal, parietal and occipital cotexes and hippocampus. There were 28 investigated seizures for each recording. Six time intervals of length 2 s were considered, starting from baseline, then preictal, begin of seizure, middle of seizure, immediately before the termination and after it. Distributions of lag for different records were compared statistically. Conclusion. The lag distribution unification for different animals was detected at the seizure beginning, with distributions from records of the same animal being usually closer than for different ones. This unification is expressed in the parietal cortex least of all. In the frontal cortex and hippocampus the unification ends with the seizure, while in the occipital cortex it remains even after seizure termination.

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Received: 
19.11.2019
Accepted: 
29.12.2019
Published: 
26.02.2020