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Universal Design for Learning (UDL) has been proposed to facilitate the training processes and improve the learning outcome. The article reviews the theories in neuroscience-based learning and evidences of brain imaging studies that relates to the principles and design of UDL. Neuroimaging based assessment strategy is also reviewed as it may provide an objective means of evaluating learning outcomes...
We investigated the performance of a new sparse neuroimaging method, i.e., Variation-Based Sparse Cortical Current Density (VB-SCCD) using magnetoencephalography (MEG) data to reconstruct extended cortical sources and their spatial distributions on the cortical surface. We conducted Monte Carlo simulation studies to compare the performance of the VB-SCCD method with different number of cortical sources...
We have previously reported a new sparse neuroimaging method (i.e. VB-SCCD) using the L1-norm optimization technology to solve EEG inverse problems. The new method distinguishes itself from other reported L1-norm methods since it explores the sparseness in a transform domain rather than in the original source domain. In the present study, we conducted a Monte Carlo simulation study to compare the...
This article provides a brief review of the state-of-the-art of EEG inverse problem in several important areas. Developments in Laplacian mapping, cortical imaging, dipole source localization, and distributed source estimation are covered. It is our intent to provide an overall introduction instead of exhaustive review of this fascinating field in this short article.
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