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Matematicheskaya Biologiya i Bioinformatika, 2017, Volume 12, Issue 2, Pages 317–326
DOI: https://doi.org/10.17537/2017.12.317
(Mi mbb296)
 

This article is cited in 9 scientific papers (total in 9 papers)

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Comparative analysis of methods for estimation of undirected coupling from time series of intracranial EEGs of cortex of rats-genetic models of absence epilepsy

A. A. Grishchenkoa, C. M. van Rijnb, I. V. Sysoevca

a Saratov State University, Saratov, Russia
b Radboud University Nijmegen, Donders Institute, Nijmegen, the Netherlands
c Saratov Branch of V.A. Kotelnikov Institute of Radioengineering and Electronics of RAS, Saratov, Russia
Full-text PDF (669 kB) Citations (9)
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Abstract: Studying coupling between brain areas from its electromagnetic activity is one of the key approaches in epilepsy research now, since epileptic activity has been considered to be a result of pathological synchronization in the brain. Often, research is conducted on animal models, because this allows to perform intracranial measurement, and to get rid of interference caused by the skull and to receive signals from deeper regions of the brain such as thalamus or hippocampus. In this study, the intracranial recordings from the frontal and parietal areas of cortex are investigated with a nonlinear correlation coefficient and a mutual information function in a sliding time window. The coupling estimates obtained were subjected for statistical analysis for significance using surrogate data. The dynamics of connectivity between the frontal cortex and the parietal cortex was shown to vary from seizure to seizure and from animal to animal. Therefore, estimates of the significant change in connectivity associated with initiation of the absense seizure, found previously based on averaging over a large number of animals and a large number of seizures for an each animal, can be a result of contribution of a relatively small number of seizures (less than a half of considered), for which the changes are significant.
Key words: epilepsy, electroencephalography, nonlinear correlation, mutual information function, surrogate data.
Received 27.06.2017, 05.08.2017, Published 05.10.2017
Document Type: Article
UDC: 123.4
Language: Russian
Citation: A. A. Grishchenko, C. M. van Rijn, I. V. Sysoev, “Comparative analysis of methods for estimation of undirected coupling from time series of intracranial EEGs of cortex of rats-genetic models of absence epilepsy”, Mat. Biolog. Bioinform., 12:2 (2017), 317–326
Citation in format AMSBIB
\Bibitem{GriVanSys17}
\by A.~A.~Grishchenko, C.~M.~van Rijn, I.~V.~Sysoev
\paper Comparative analysis of methods for estimation of undirected coupling from time series of intracranial EEGs of cortex of rats-genetic models of absence epilepsy
\jour Mat. Biolog. Bioinform.
\yr 2017
\vol 12
\issue 2
\pages 317--326
\mathnet{http://mi.mathnet.ru/mbb296}
\crossref{https://doi.org/10.17537/2017.12.317}
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  • This publication is cited in the following 9 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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