This study aimed to develop a time–frequency method for measuring directional interactions
over time and frequency from scalp-recorded electroencephalographic (EEG) signals in a …

In this paper, a framework is developed for the identification of causal effects from non-
stationary time series. Focusing on causality measures that make use of delay vectors from …

Exploring brain networks is an essential step towards understanding functional organization
of the brain, which needs characterization of linear and nonlinear connections based on …

This article addresses the problem of estimating brain effective connectivity from
electroencephalogram (EEG) signals using a Granger causality (GC) characterized on state …

In the context of EEG/MEG, the term'volume conduction (VC) effects' refers to the recording
of an instantaneous linear mixture of multiple brain source activities by each EEG/MEG …

In the aim to explore the complex relationships between S&P500, VIX and volume we
introduce a Granger causality test using the nonlinear statistic of Asymmetric Partial Transfer …

Background Despite the variety of effective connectivity measures, few methods can quantify
direct nonlinear causal couplings and most of them are not applicable to high-dimensional …

The majority of previous functional/effective connectivity studies conducted on the autistic
patients converged to the underconnectivity theory of ASD:“long-range underconnectivity …

In this study, an asynchronous artifact-enhanced electroencephalogram (EEG)-based
control paradigm assisted by slight-facial expressions (sFE-paradigm) was developed. The …

The aim of this study is to develop a time-frequency method and test its applicability to
investigating directional cortical connectivity in the newborn brain considering the effect of …