Abstract
In spite of important technological developments in the medical field and particularly in neuroscience one, epilepsy remained a serious pathology that could affect the human brain. In this work, we modeled a healthy and an epileptic cerebral activity in rest state. We used, the virtual brain TVB toolbox to simulate the two states based on FHN and epileptor model. We compared phase plane spaces, electrophysiological time series (electroencephalogram EEG, magnetoencephalogram MEG and intracerabral EEG), specter of eigenvalues transition matrix and topographic maps for healthy and epileptic rest state. There is a unique metastable state for healthy cerebral dynamics convergence which disappears in epileptic cerebral dynamics. Epileptic rest state time series depicts several transitory activities that vanish in the normal state. Normal rest state topographic maps illustrate a limited dipolar activity; which is more extended in epileptic model. These prominent differences would have an important impact on real cerebral activities analysis.
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References
Fisher, R.S., van Emde Boas, W., Blume, W., Elger, C., Genton, P., Lee, P., et al.: Epileptic seizures and epilepsy: definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE). Epilepsia 46, 470–472 (2005)
Jmail, N., Gavaret, M., Bartolomei, F., Chauvel, P., Badier, J.M., Bnar, C.-G.: Comparison of brain networks during interictal oscillations and spikes on magnetoencephalography and intracerebral EEG. Brain Topogr. 29, 752–765 (2016)
Jmail, N., Gavaret, M., Bartolomei, F., Bnar, C.-G.: Despiking SEEG signals reveals dynamics of gamma band preictal activity. Physiol. Meas. 38, 42–56 (2017)
Jackson, J.H.: On the scientific and empirical investigation of epilepsies. Med. Press Circ. (Ed.) 18, 325–327 (1874)
ILAE: Proposal for revised classification of epilepsies and epileptic syndromes. Commission on classification and terminology of the International League Against Epilepsy. Epilepsia 30, 389–399 (1989)
Grouiller, F.: Cartographie fonctionnelle du cerveau pileptique lors des valuations pr chirurgicales. Institut des Neuroscience de Grenoble (2008)
Hamandi, K., Salek-Haddadi, A., Laufs, H., Liston, A., Friston, K., Fish, D.R., Duncan, J.S., Lemieux, L.: EEG-fMRI of idiopathic and secondarily generalized epilepsies. Neuroimage 31, 1700–1710 (2006)
Jirsa, V., Jantzen, K., Fuchs, A., Kelso, J.: Spatiotemporal forward solution of the EEG and MEG using network modeling. IEEE Trans. Med. Imag. 21, 493–504 (2002). https://doi.org/10.1109/TMI.2002.1009385
FitzHugh, R.: Impulses and physiological states in theoretical models of nerve membrane. Biophysical J. 1, 445–466 (1961)
Jirsa, V.K., Stacey, W.C., Quilichini, P.P., Ivanov, A.I., Bernard, C.: On the nature of seizure dynamics. Brain J. Neurol. 137, 1–21 (2014)
Hadriche, A., Pezard, L., Nandrino, J., Ghariani, H., Kachouri, A., Jirsa, K.: Mapping the dynamic repertoire of the resting brain. Neuro Image J. 78, 448–462 (2013)
Hadriche, A., Jmail, N., Elleuch, R., Pzard, L.: Different methods for partitioning the phase space of dynamic system. IJCA 93(15), May 2014
Jmail, N., Gavaret, M., Wendling, F., Kachouri, A., Hamadi, G., Badier, J.-M., Bnar, C.-G.: A comparison of methods for separation of transient and oscillatory signals in EEG. J. Neurosci. Methods 199(2), 273–289 (2011)
Jmail, N., Gavaret, M., Bartolomei, F., Bnar, C.-G.: Despikifying SEEG signals using a temporal basis set. In: The International Conference on Intelligent Systems Design and Applications, Marrakech, Moroco (2015)
Hadriche, A., Jmail, N., Ghariani, H., Kachouri, A., Pezard, L.: Reduction of continuous neuronal model to discrete binary automata. Int. J. Comput. Appl. 69(24), 5–10 (2013a). Published by Foundation of Computer Science, New York, USA
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Jarray, R., Jmail, N., Hadriche, A., Frikha, T. (2018). A Comparison Between Modeling a Normal and an Epileptic State Using the FHN and the Epileptor Model. In: Abraham, A., Haqiq, A., Muda, A., Gandhi, N. (eds) Innovations in Bio-Inspired Computing and Applications. IBICA 2017. Advances in Intelligent Systems and Computing, vol 735. Springer, Cham. https://doi.org/10.1007/978-3-319-76354-5_22
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DOI: https://doi.org/10.1007/978-3-319-76354-5_22
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