Abstract
While visualization of brain activity has well established practical applications such as real-time functional mapping or neurofeedback, visual representation of brain connectivity is not widely used. In addition, technically challenging single-trial connectivity estimation may have hindered practical usage of connectivity in online applications. In this work, we developed algorithms that are capable of estimating and visualizing (effective) connectivity between independent cortical sources during online EEG recordings. The core routines of our procedure, such as CSPVARICA source extraction and regularized connectivity estimation, are available in our open source Python-based toolbox SCoT. We demonstrate for the first time that online connectivity visualization is feasible. We show this in a feasibility study with twelve participants performing two different tasks, namely motor execution and resting with eyes open or closed. Connectivity patterns were significantly different between two motor tasks in four participants, whereas significant differences between resting task patterns were found in seven participants. Existing connectivity studies have focused on offline methods. In contrast, there are only a small number of exampl...Continue Reading
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Sep 22, 2019·Biomedizinische Technik. Biomedical Engineering·Mehdi RajabiounRobert Coben
Aug 31, 2017·Australasian Physical & Engineering Sciences in Medicine·Mehdi RajabiounMohammad Bagher Shamsollahi
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