We propose a new measure of synchronization of multichannel ictal and interictal EEG signals. The measure is based on the residual covariance matrix of a multichannel autoregressive model. A major advantage of this measure is its ability to be interpreted both in the framework of stochastic and deterministic models. A preliminary analysis of EEG data from three patients using this measure documents the expected increased synchronization during ictal periods but also reveals that increased synchrony persists for prolonged periods (up to 2 hours or more) in the postictal period. Key words: neural synchronization, epilepsy, multichannel autoregressive model, nonlinear dynamics, seizure 1 Introduction Epileptic seizures are by nature episodic e...
Real world biological systems such as the human brain are inherently nonlinear and difficult to mode...
Phase synchrony assessment across non-stationary multivariate signals is a useful way to characteriz...
International audienceIn this paper, a model-based approach is presented to quantify the effective s...
In this paper we introduce a novel method for the characterization of synchronziation and coupling e...
Complex biological systems such as the human brain can be expected to be inherently nonlinear and he...
Synchronization behavior of electroencephalographic (EEG) signals is important for decoding informat...
The chapters thus far have described quantitative tools that can be used to extract information from...
The pathways by which epileptic seizures propagate through the brain are unknown. Since the speed of...
There are various methods to measure the value of synchronization of signals. These methods usually ...
Cognitive processing requires integration of information processed simultaneously in spatially disti...
During the last years methods from nonlinear time series analysis have been successfully applied in ...
Summarization: Epilepsy is one of the most common brain disorders and may result in brain dysfunctio...
Synchronization is an important mechanism that helps in understanding information processing in a no...
The question whether information extracted from the electroencephalogram ~EEG! of epilepsy patients ...
AbstractWe investigate the emergence of synchronization in two groups of oscillators; one group acts...
Real world biological systems such as the human brain are inherently nonlinear and difficult to mode...
Phase synchrony assessment across non-stationary multivariate signals is a useful way to characteriz...
International audienceIn this paper, a model-based approach is presented to quantify the effective s...
In this paper we introduce a novel method for the characterization of synchronziation and coupling e...
Complex biological systems such as the human brain can be expected to be inherently nonlinear and he...
Synchronization behavior of electroencephalographic (EEG) signals is important for decoding informat...
The chapters thus far have described quantitative tools that can be used to extract information from...
The pathways by which epileptic seizures propagate through the brain are unknown. Since the speed of...
There are various methods to measure the value of synchronization of signals. These methods usually ...
Cognitive processing requires integration of information processed simultaneously in spatially disti...
During the last years methods from nonlinear time series analysis have been successfully applied in ...
Summarization: Epilepsy is one of the most common brain disorders and may result in brain dysfunctio...
Synchronization is an important mechanism that helps in understanding information processing in a no...
The question whether information extracted from the electroencephalogram ~EEG! of epilepsy patients ...
AbstractWe investigate the emergence of synchronization in two groups of oscillators; one group acts...
Real world biological systems such as the human brain are inherently nonlinear and difficult to mode...
Phase synchrony assessment across non-stationary multivariate signals is a useful way to characteriz...
International audienceIn this paper, a model-based approach is presented to quantify the effective s...