Electrophysiological source imaging (ESI) has been successfully employed in many brain
imaging applications during the last 20 years. ESI estimates of underlying brain networks …

EEG inverse problem is underdetermined, which poses a long standing challenge in
Neuroimaging. The combination of source-imaging and analysis of cortical directional …

In this article, we investigate brain directed connectivity (BDC) networks for emotion
recognition using electroencephalogram (EEG) source signals that were estimated from …

Objective: Electroencephalography (EEG) and magnetoencephalography noninvasively
record scalp electromagnetic fields generated by cerebral currents, revealing millisecond …

Electromagnetic brain imaging is the reconstruction of brain activity from non-invasive
recordings of the magnetic fields and electric potentials. An enduring challenge in this …

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 …

Objective: The electroencephalographic (EEG) inverse problem is ill-posed owing to the
electromagnetism Helmholtz theorem and since there are fewer observations than the …

Electroencephalographic (EEG) source imaging (ESI) is a powerful method for studying
brain functions and surgical resection of epileptic foci. However, accurately estimating the …

In this paper, we present a novel hierarchical multiscale Bayesian algorithm for
electromagnetic brain imaging using magnetoencephalography (MEG) and …

Source imaging of Electroencephalography (EEG) and Magnetoencephalography (MEG)
provides a noninvasive way of monitoring brain activities with high spatial and temporal …