MEG

Electrophysiological Brain Connectivity: Theory and Implementation

Electrophysiological Brain Connectivity: Theory and Implementation

Author(s)3: Bin He, Laura Astolfi, Pedro Antonio Valdés-Sosa, Daniele Marinazzo, Satu O. Palva, Christian-George Bénar, Christoph M. Michel, Thomas Koenig
Electrophysiological Brain Connectivity: Theory and Implementation 170 177 IEEE Transactions on Biomedical Engineering (TBME)

Brain function and dysfunction are encoded in networks within the brain that are distributed over 3-dimensional space and evolves in time. It is of great importance to image brain activation…

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Electromagnetic Brain Source Imaging by Means of a Robust Minimum Variance Beamformer

Author(s)3: Seyed Amir Hossein Hosseini, Abbas Sohrabpour, Mehmet Akçakaya, Bin He
Electromagnetic Brain Source Imaging by Means of a Robust Minimum Variance Beamformer 170 177 IEEE Transactions on Biomedical Engineering (TBME)

Adaptive beamformer methods have been used extensively for functional brain imaging using EEG/MEG surface recordings. However, the sensitivity of beamformers to model mismatches impedes their widespread application, in practice. In…

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Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach

Author(s)3: Abbas Sohrabpour, Shuai Ye, Gregory A. Worrell, Wenbo Zhang, Bin He
Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach 170 177 IEEE Transactions on Biomedical Engineering (TBME)

Abbas Sohrabpour, Shuai Ye, Gregory Worrell, Wenbo Zhang, Bin He, University of Minnesota, USA Electromagnetic source imaging (ESI) techniques are very efficient in determining the foci of activity from surface…

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Single-Trial Detection with Magnetoencephalography During a Dual Rapid Serial Visual Presentation Task

Author(s)3: Hubert Cecotti
Single-Trial Detection with Magnetoencephalography During a Dual Rapid Serial Visual Presentation Task 170 177 IEEE Transactions on Biomedical Engineering (TBME)

Hubert Cecotti, Ulster University, UK The detection of brain responses corresponding to the presentation of a particular class of images is a challenge in Brain-Machine Interface (BMI). Current systems based on…

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