Electrophysiological Brain Connectivity: Theory and Implementation
In this tutorial paper, we describe the theoretical basis, computational algorithms, and applications of dynamic functional brain connectivity analysis from electromagnetic measurements, including electroencephalography (EEG), magnetoencephalography (MEG), electrocorticography (ECoG), and stereoelectroencephalography (SEEG). Various connectivity estimators are discussed, and algorithms introduced. The merits, limitations, and needs for future development are also discussed. The tutorial will serve both new comers and practitioners working on brain connectivity analysis.
Three-Dimensional Brain-Computer Interface Control through Simultaneous Overt Spatial Attentional and Motor Imagery Tasks
We propose a novel task utilizing the endogenous modulation of visuospatial attention, i.e., overt spatial attention (OSA), and demonstrate similar control to conventional MI based BCI. Furthermore, through the combination of the two strategies (MI and OSA) a substantial portion of the recruited subjects were capable of robustly controlling a virtual cursor in 3D space.
Electromagnetic Brain Source Imaging by Means of a Robust Minimum Variance Beamformer
We propose a technique called robust minimum variance beamformer (RMVB) which enables adaptive beamformers to remain robust against model non-idealities in the lead-field matrix. RMVB yields robustness by quantifying different model uncertainties as hyper-dimensional ellipsoids. These uncertainty regions, which can be estimated empirically by building several forward models, are then directly incorporated in the equations to estimate the spatial-filter weights which will be subsequently used for imaging.
Localization of Origins of Premature Ventricular Contraction by Means of Convolutional Neural Network from 12-lead ECG
We proposes a novel method to localize origins of premature ventricular contractions (PVCs) from 12-lead ECG using convolutional neural network (CNN) and a realistic computer heart model. The proposed method consists of two CNNs to classify among ventricular sources from 25 segments and from epicardium (Epi) or endocardium (Endo). …
Electrical Properties Tomography Based on B1 Maps in MRI: Principles, Applications, and Challenges
We review the basic principle of electrical properties tomography (EPT), reconstruction methods, biomedical applications including tumor imaging, and existing challenges. As an important application of EPT, the estimation of specific absorption rate (SAR) and its current development will also be discussed.
Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach
We present an electrophysiological connectome (eConnectome) approach to study underlying brain networks in a noninvasive manner. This approach was directly tested by estimating epileptic networks from EEG/MEG measurements in patients suffering from focal epilepsy. The results obtained from the proposed approach were consistent with invasive clinical findings, in these patients.