A systems-level approach to human epileptic seizures.

Epileptic seizures are due to the pathological collective activity of large cellular assemblies. A better understanding of this collective activity is integral to the development of novel diagnostic and therapeutic procedures. In contrast to reductionist analyses, which focus solely on small-scale characteristics of ictogenesis, here we follow a systems-level approach, which combines both small-scale and larger-scale analyses.

Assessing periodicity of periodic leg movements during sleep.

Background: Periodic leg movements (PLM) during sleep consist of involuntary periodic movements of the lower extremities. The debated functional relevance of PLM during sleep is based on correlation of clinical parameters with the PLM index (PLMI). However, periodicity in movements may not be reflected best by the PLMI.

Analyzing spatio-temporal patterns of genuine cross-correlations.

In multivariate time series analysis, the equal-time cross-correlation is a classic and computationally efficient measure for quantifying linear interrelations between data channels. When the cross-correlation coefficient is estimated using a finite amount of data points, its non-random part may be strongly contaminated by a sizable random contribution, such that no reliable conclusion can be drawn about genuine mutual interdependencies. The random correlations are determined by the signals' frequency content and the amount of data points used.

Peri-ictal correlation dynamics of high-frequency (80-200 Hz) intracranial EEG.

Purpose: To assess (1) how large-scale correlation of intracranial EEG signals in the high-frequency range (80-200Hz) evolves from the pre-ictal, through the ictal into the postictal state and (2) whether the contribution of local neuronal activity to large-scale EEG correlation differentiates epileptogenic from non-epileptogenic brain tissue.

Methods: Large-scale correlation of intracranial EEG was assessed by the total correlation strength (TCS), a measure derived from the eigenvalue spectra of zero-lag correlation matrices computed in a time-resolved manner by using a moving window approach. The relative change of total correlation strength (Delta(j)) resulting from leaving out EEG channel j ("leave-one-out approach") was used to quantify the contribution of local neuronal activity to large-scale EEG correlation.

Cortical local and long-range synchronization interplay in human absence seizure initiation.

Brain activity relies on transient, fluctuating interactions between segregated neuronal populations. Synchronization within a single and between distributed neuronal clusters reflects the dynamics of these cooperative patterns. Thus absence epilepsy can be used as a model for integrated, large-scale investigation of the emergence of pathological collective dynamics in the brain.

Exploring the dynamics of collective synchronizations in large ensembles of brain signals.

Developing methods characterizing the dynamics of synchronization in large ensemble of electromagnetic brain signals has become an important issue. In this article, we review a recently introduced method for analyzing multivariate phase synchronization in brain signals. The approach is based on the equivalence between phase locking and frequency locking in narrow band signals, which allows tracking multivariate phase synchronization in the time-frequency domain as periods of common frequency among multiple channels.