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Lecture Notes in Computer Science
Despite the clear potential benefits of combining fMRI and diffusion MRI in learning the neural pathways that underlie brain functions, little methodological progress has been made in this direction. In this paper, we propose a novel multimodal integration approach based on sparse Gaussian graphical model for estimating brain connectivity. Casting functional connectivity estimation as a sparse inverse covariance learning problem, we adapt the level of sparse penalization on each connectiondoi:10.1007/978-3-642-33415-3_87 fatcat:byrnkq7kjjh4ddxfhukccnjrmy