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A post-processing method for group discriminant analysis of fMRI is proposed. It assumes that the fMRI data have been pre-processed and analyzed so that each voxel is given a statistic specifying task-related activation(s), and that individually specific regions of interest (ROIs) have been drawn for each subject. The method then utilizes Local Linear Discriminant Analysis (LLDA) to jointly optimize...
Large intersubject variability is a well-described feature of fMRI studies, making inter-group inference, of critical importance for biological interpretation, difficult. Therefore, traditional approaches involve spatially transforming the data of each subject and heavily spatially smoothing the data. Here we propose an alternate method: after first defining individually-specific Regions of Interest...
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