Spatially adaptive multivariate methods were applied in fMRI activation analysis to alleviate low sensitivity in commonly used Gaussian smoothing single voxel analysis. Usually these methods require constraint to avoid the curse of high degrees of freedom. We have developed a novel spatially adaptive kernel canonical correlation analysis method, which does not require constraint and has superior performance compared to other methods.
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