In this primer, we give a review of the inverse problem for EEG source localization. This is
intended for the researchers new in the field to get insight in the state-of-the-art techniques …

This article reviews progress and challenges in model driven EEG/fMRI fusion with a focus
on brain oscillations. Fusion is the combination of both imaging modalities based on a …

We review the theory and algorithms of electrophysiological brain connectivity analysis. This
tutorial is aimed at providing an introduction to brain functional connectivity from …

Scalp electric potentials (electroencephalogram; EEG) are contingent to the impressed
current density unleashed by cortical pyramidal neurons undergoing post-synaptic …

This is the final paper in a Comments and Controversies series dedicated to “The
identification of interacting networks in the brain using fMRI: Model selection, causality and …

Many different analysis techniques have been developed and applied to EEG recordings
that allow one to investigate how different brain areas interact. One particular class of …

We propose a novel ℓ1ℓ2-norm inverse solver for estimating the sources of EEG/MEG
signals. Based on the standard ℓ1-norm inverse solvers, this sparse distributed inverse …

Dynamical causal modeling (DCM) of evoked responses is a new approach to making
inferences about connectivity changes in hierarchical networks measured with electro-and …

Fatigue driving is bringing more and more serious harm, but there are various reasons for
fatigue driving, it is still difficult to test the driver's fatigue. This paper defines a method to test …

Inference and simulation in the context of high-dimensional dynamical systems remain
computationally challenging problems. Some form of dimensionality reduction is required to …