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

The fault-induced impulse responses of localized bearing fault are usually interfered by the
background noise and other harmonic components. They are strongly coupled together and …

Identifying the functional networks underpinning indirectly observed processes poses an
inverse problem for neurosciences or other fields. A solution of such inverse problems …

Using deep neural networks (DNNs) to explore spatial patterns and temporal dynamics of
human brain activities has been an important yet challenging problem because the artificial …

Functional near-infrared spectroscopy (fNIRS) is a non-invasive imaging technique that
elicits growing interest for research and clinical applications. In the last decade, efforts have …

Source localization of focal electrical activity from scalp electroencephalogram (sEEG)
signal is generally modeled as an inverse problem that is highly ill-posed. In this paper, a …

Oscillatory processes at all spatial scales and on all frequencies underpin brain function.
Electrophysiological Source Imaging (ESI) is the data-driven brain imaging modality that …

We have identified an electroencephalographic (EEG) based statistical classifier that
correctly distinguishes children with histories of Protein Energy Malnutrition (PEM) in the first …

The Tomographic Quantitative Electroencephalography (qEEGt) toolbox is integrated with
the Montreal Neurological Institute (MNI) Neuroinformatics Ecosystem as a docker into the …

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