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• W2051244705 abstract "To combine functional neuroimaging studies across subjects, anatomical and functional data are typically either transformed to a common space or averaged across regions of interest (ROIs). However, if there are (1) anatomical variations within the subject pool (as in clinical or aging populations), (2) non-Gaussian distributions of task-related activity within a typical ROI or, (3) more ROIs than subjects, neither spatial transformation of the data to a common space nor averaging across all subjects' ROIs is suitable for standard discriminant analysis. To solve these problems, we describe a post-processing method that uses voxel-based statistics representing task-related activity (pooled within ROIs) to establish combinations of ROIs that maximally differentiate tasks across all subjects. The method involves randomized resampling from multiple ROIs within each subject, multivariate linear discriminant analysis across all subjects and validation with bootstrapping techniques. When applied to experimental data from healthy subjects performing two motor tasks, the method detected some brain regions, including the supplementary motor area (SMA), that participated in a distributed network differentially active between tasks. However there was not a significant difference in SMA activity when this region was examined in isolation. We suggest this method is a practical means to combine voxel-based statistics within anatomically defined ROIs across subjects." @default.
• W2051244705 created "2016-06-24" @default.
• W2051244705 creator A5029737751 @default.
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• W2051244705 date "2004-05-01" @default.
• W2051244705 modified "2023-09-25" @default.
• W2051244705 title "A post-processing/region of interest (ROI) method for discriminating patterns of activity in statistical maps of fMRI data" @default.
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• W2051244705 doi "https://doi.org/10.1016/j.jneumeth.2003.12.021" @default.
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