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Working memory (WM) is particularly important for higher cognitive tasks. Previous studies have shown that there are several brain networks under WM task or training, however, it is still unknown how many networks are involved in WM. In this paper, we utilize the method of modularity in the graph theory to explore the module distribution and the degree of coupling of the brain network under the real-time...
The default mode network (DMN) is a network of brain regions that are active during rest and suppressed during a cognitively demanding task. Previous studies have shown that the DMN can be altered by development, aging, disorder, cognitive tasks and offline training. However, it's unclear whether activity in the DMN can be altered by real-time training. Recently, real-time functional magnetic resonance...
In BCI research community, support vector machine (SVM) is an effective method for motor imagery (MI)-based electroencephalographic (EEG) classification. However, the computation of decision function during SVM classification stage for a new EEG trial is time-consuming due to the large number of support vectors (SV). This paper proposes a new method to reduce the number of support vectors so that...
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