Titlebook: Brain Informatics; International Confer Shouyi Wang,Vicky Yamamoto,Tom Mitchell Conference proceedings 2018 Springer Nature Switzerland AG

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https://doi.org/10.1057/978-1-137-52095-1research and clinic applications due to its convenient implementation and modulation of the brain functionality. In this paper, we propose a novel multi-electrode tDCS current configuration model that minimizes the total error under the safety constraints. After rewriting the model as a linearly con

把手

https://doi.org/10.1057/978-1-137-52095-1signing the set of Regions-of-interest (ROIs) over the cortical surface, (ii) estimating the ROI time-courses using a dynamic inverse problem formulation, (iii) estimating the pairwise functional connectivity between ROIs, and (iv) feeding a Support Vector Machine Classifier with the estimated conne

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https://doi.org/10.1007/978-1-4842-2214-0formation belonging to each EEG channel. Nevertheless, several studies have characterized cognitive functions as synchronized brain networks depending on the underlying neural interactions. As a result, connectivity analysis provides essential information for improving both the interpretation and in

Misnomer

https://doi.org/10.1007/978-1-4842-2214-0t an imagined spatial perspective) represent the two most well-known and used types of spatial transformation. Yet, these two spatial transformations are conceptually, visually, and mathematically equivalent. Thus, an active debate in the field is whether these two types of spatial transformations a

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Peng Wu,Hao Xu,Le Xu,Yueming Liu,Mingyuan Hement imagery tasks, as well as the directionality of such coupling. For this, we consider the multivariate autoregressive model of the signals from a selection of eleven EEG channels that are assumed as a fully-connected measurement network. Then, we aim to find differences in connectivity patterns

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