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In the statistical analysis of functional brain imaging data, regression analysis and cross correlation analysis between time series data on each grid point have been widely used. The results can be graphically represented as an activation map on an anatomical image, but only activation signal, whose temporal pattern resembles the predefined reference function, can be detected. In the present study,...
We introduce an anatomical and electrophysiological model of deep brain structures dedicated to magnetoencephalography (MEG) and electroencephalography (EEG) source imaging. So far, most imaging inverse models considered that MEG/EEG surface signals were predominantly produced by cortical, hence superficial, neural currents. Here we question whether crucial deep brain structures such as the basal...
We have developed an fMRI-MEG integrative neuroimaging method that is capable of analyzing spatiotemporal multiple cortical activities. The method determines the center of gravity in each fMRI activated cluster as the location of the linear constraints. First, activated multiple clusters were determined by statistically analyzing fMRI data. Secondly, using the fMRI activated clusters as spatial constraints,...
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