DYNAMICS OF LOCAL POTENTIALS OF BRAIN AT THE ABSENCE-EPILEPSY: EMPIRICAL MODELLING
Cite this article as:
Filina Е. V. DYNAMICS OF LOCAL POTENTIALS OF BRAIN AT THE ABSENCE-EPILEPSY: EMPIRICAL MODELLING. Izvestiya VUZ. Applied Nonlinear Dynamics, 2011, vol. 19, iss. 4, pp. 109-123. DOI: https://doi.org/10.18500/0869-6632-2011-19-4-109-123
The EEG research technique on the basis of autoregressive models construction and Granger causality estimation by experimental data are described in this article. The EEG is written down from the brain of WAG/Rij rats, which are absence-epilepsy contaminated. The EEG episodes well enough described in terms of small order linear display along with the episodes with expressed nonlinearity are revealed during the analysis. The EEG episodes ordering is spent in accordance with the model parameters received and physio-logical condition of the animals. It is reveled that dynamics becomes easier to predict in comparison to the condition of passive wakefulness before the epilepsy attack. Deep brain structures influence enhancement on the cortex and brain structures influence decrease on the reticular kernel before the attack is established.
1. Зенков Л.Р. Клиническая электроэнцефалография (с элементами эпилептологии). Таганрог: Изд-во ТРТУ, 1996.
2. Knyazeva M.G. et al. Psychogenic seizures and frontal disconnection: EEG synchronisation study // J. Neurol. Neurosurg. Psychiatry, May 2011. Vol. 82. P. 505.
3. Fellinger R., Klimesch W. et al. Cognitive processes in disorders of consciousness as revealed by EEG time-frequency analyses. Clinical Neurophysiology. 2011. P. 8.
4. Coenen A.M.L., Van Luijtelaar E.L.J.M. The WAG/Rij rat model for absence epilepsy: age and sex factors // Epilepsy Res. 1987. Vol. 1. P. 297.
5. Van Luijtelaar E.L.J.M., Coenen A.M.L. The WAG/Rij model for generalized absence epilepsy // Adv. in Epileptol. 1989. Vol. 17. P. 16.
6. De Bruin N.M.W.J., Van Luijtelaar E.L.J.M., Jansen S.J., Cools A.R., Ellenbroek B.A. Dopamine characteristics in different rat genotypes: the relation to absence epilepsy // Neuroscience Res. 2000. Vol. 38. P. 165.
7. Sitnikova E., van Luijtelaar G. Cortical and thalamic coherence during spike-wave seizures in WAG/Rij rats // Epilepsy Res. 2006. Vol. 71(2-3). P. 159.
8. Sitnikova E., van Luijtelaar G. Cortical control of generalized absence seizures: effect oflidocaine applied to the somatosensory cortex in WAG/Rij rats // Brain Res. 2004. Vol. 1012(1-2). P. 127.
9. Gloor P. Generalized cortico-reticular epilepsies. Some considerations on the pathophysiology of generalized bilaterally synchronous spike and wave discharge // Epilepsia 9. 1968. P. 249.
10. Sitnikova E., Dikanev T., Smirnov D., Bezruchko B.P., van Luijtelaar G. Granger causality: Cortico-thalamic interdependencies during absence seizures in WAG/Rij rats // J. Neurosci. Methods. 2008. Vol. 170(2). P. 245.
11. Schwartz G. Estimating the order of a model // Ann. Stat. 1978. Vol.6. P. 461.
12. Granger C.W.J. Investigating causal relations by econometric models and crossspectral methods // Econometrica. 1969. Vol. 37. P. 424.
13. Seber G.A.F. Linear regression analysis. John Wiley and Sons, 1977.
BibTeX
author = {Е. V. Filina },
title = {DYNAMICS OF LOCAL POTENTIALS OF BRAIN AT THE ABSENCE-EPILEPSY: EMPIRICAL MODELLING},
year = {2011},
journal = {Izvestiya VUZ. Applied Nonlinear Dynamics},
volume = {19},number = {4},
url = {https://old-andjournal.sgu.ru/en/articles/dynamics-of-local-potentials-of-brain-at-the-absence-epilepsy-empirical-modelling},
address = {Саратов},
language = {russian},
doi = {10.18500/0869-6632-2011-19-4-109-123},pages = {109--123},issn = {0869-6632},
keywords = {Autoregressive model,Granger causality,absance-epilepsy,EEG,Wag/Rij rats.},
abstract = {The EEG research technique on the basis of autoregressive models construction and Granger causality estimation by experimental data are described in this article. The EEG is written down from the brain of WAG/Rij rats, which are absence-epilepsy contaminated. The EEG episodes well enough described in terms of small order linear display along with the episodes with expressed nonlinearity are revealed during the analysis. The EEG episodes ordering is spent in accordance with the model parameters received and physio-logical condition of the animals. It is reveled that dynamics becomes easier to predict in comparison to the condition of passive wakefulness before the epilepsy attack. Deep brain structures influence enhancement on the cortex and brain structures influence decrease on the reticular kernel before the attack is established. }}