Assessing seizure dynamics by analysing the correlation structure of multichannel intracranial EEG

Abstract

Epileptic seizures are commonly characterized as 'hypersynchronous states'. This habit is doubly misleading, because seizures are not necessarily synchronous and are not unchanging 'states' but dynamic processes. Here the temporal evolution of the correlation structure in the course of 100 focal onset seizures of 60 patients recorded by intracranial multichannel EEG was assessed. To this end a multivariate method was applied that at its core consists of computing the eigenvalue spectrum of the zero-lag correlation matrix of a short sliding window. Our results show that there are clearly observable and statistically significant changes of the correlation structure of focal onset seizures. Specifically, these changes indicate that the zero-lag correlation of multi-channel EEG either remains approximately unchanged or-especially in the case of secondary generalization-decreases during the first half of the seizures. Then correlation gradually increases again before the seizures terminate. This development was qualitatively independent of the anatomical location of the seizure onset zone and therefore seems to be a generic property of focal onset seizures. We suggest that the decorrelation of EEG activity is due to the different propagation times of locally synchronous ictal discharges from the seizure onset zone to other brain areas. Furthermore we speculate that the increase of correlation during the second half of the seizures may be causally related to seizure termination.

Multiscaled Cross-Correlation Dynamics on SenseCam Lifelogged Images

“…for financial series [9][10][11][12][13][14][15][16][17][18][19][20], electroencephalographic (EEG) recordings [21,22], magnetoencephalographic (MEG) recordings [23] and a variety of other multivariate data. In this paper, we investigate the same approach to analysis SenseCam lifelog data streams.…”

Chow–Liu trees are sufficient predictive models for reproducing key features of functional networks of periictal EEG time-series

“…Along different lines of evidence, moreover, eigenvector analysis has indicated that towards seizure end such an initial desynchronization is followed by a reconfiguring hypersynchronization phase, which may thus even play a beneficial role as a mechanism for seizure termination (Schindler et al, 2007). These findings constitute a departure from the traditional view, which considers seizures as events of temporally constant, global hypersynchrony (Schindler et al, 2007).…”

“…Along different lines of evidence, moreover, eigenvector analysis has indicated that towards seizure end such an initial desynchronization is followed by a reconfiguring hypersynchronization phase, which may thus even play a beneficial role as a mechanism for seizure termination (Schindler et al, 2007). These findings constitute a departure from the traditional view, which considers seizures as events of temporally constant, global hypersynchrony (Schindler et al, 2007). Also, our result regarding the epoch course of the Shannon entropy lends further support against the hypothesis of constant, global hypersynchrony during seizures, since synchronous processes are associated with low entropy which, in contrast, we found to be largest at ictal mid-time.…”

“…A longstanding view in epilepsy research is to regard seizures as states of global hypersynchrony in the EEG, such that the degree of synchronicity between subsets of electrodes stays constantly high during the seizure and is independent of seizure epoch (Schindler et al, 2007). Therefore, we were interested in the periictal evolution of the Shannon entropy H(x), as this measure may be used for characterizing synchronicity in case of EEG data.…”

“…In terms of the underlying EEG signals, this indicates a dynamical shift during early seizure development towards locally highly synchronized 'islands' of EEG activity, that are desynchronized amongst each other. These and related findings (Schindler et al, 2007) have lead to a paradigm shift in epilepsy research, which had previously been dominated by the idea of seizures being events of temporally constant, global hypersynchrony (Schindler et al, 2007;Jiruska et al, 2013).…”