DYNAMICS OF LINEAR AND NONLINEAR INTERRELATION NETWORKS IN PERI-ICTAL INTRACRANIAL EEG: SEIZURE ONSET AND TERMINATION (original) (raw)

Abstract

ABSTRACT During epileptic seizures a large number of neurons are recruited into a collective dynamics. Rather than being simply monolithic “hyper-synchronous states” seizures show a complex and often patient specific evolution in multichannel EEG. Here, we summarize recent approaches to a multivariate description of the whole interacting network by diagonalization of interrelation matrices. Equal-time cross-correlation and mutual information are used to estimate linear and nonlinear interrelations and appropriate surrogates are employed for hypothesis testing. It has been found that focal onset seizures stop after an increase of crosscorrelation on the largest spatial scale accessible by intracranial EEG. On smaller scales a pronounced rearrangement of correlation patterns is observed during seizures. Ictogenic brain tissue may differ from the non-ictogenic one with respect to its degree of significantly nonlinear interrelations that cannot be explained by linear correlation alone. Nonlinear interrelation tends to be higher during seizures than inter-ictally. We conclude that multivariate methods and a separation of nonlinear from linear effects may give new insights into spatio-temporal seizure dynamics. These approaches might contribute to a better understanding of seizure generation and termination as well as to a better delineation of ictogenic brain tissue. Thus, they may ultimately be relevant for novel diagnostic and therapeutic approaches.

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