The complexity of many biological, social and technological systems stems from the richness
of the interactions among their units. Over the past decades, a variety of complex systems …

In the last decade, there has been a growing body of literature addressing the utilization of
complex network methods for the characterization of dynamical systems based on time …

Multivariate time series analysis is extensively used in neurophysiology with the aim of
studying the relationship between simultaneously recorded signals. Recently, advances on …

Epilepsy is a malfunction of the brain that affects over 50 million people worldwide. Epileptic
seizures are usually characterized by an abnormal synchronized firing of neurons involved …

Transitions in the dynamics of complex systems can be characterized by changes in the
synchronization behavior of their components. Taking the human cardiorespiratory system …

The investigation of synchronization phenomena on measured experimental data such as
biological time series has recently become an increasing focus of interest. Different …

Using several methods for detection of causality in time series, we show in a numerical study
that coupled chaotic dynamical systems violate the first principle of Granger causality that …

To detect directional couplings from time series various measures based on distances in
reconstructed state spaces were introduced. These measures can, however, be biased by …

We introduce a method to detect and quantify the asymmetry of the coupling between two
interacting systems based on their recurrence properties. This method can detect the …

Based on the nonlinear techniques for estimation of coupling between oscillatory systems,
we investigate the dynamics of climatic modes characterizing global and the Northern …