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A kernel machine method for detecting effects of interaction between multidimensional variable sets: An imaging genetics application., , , , , and . NeuroImage, (2015)Genetics of the connectome., , , , and . NeuroImage, (2013)A Novel Extended Granger Causal Model Approach Demonstrates Brain Hemispheric Differences during Face Recognition Learning., , and . PLoS Computational Biology, (2009)Granger causality with signal-dependent noise., , and . NeuroImage, 57 (4): 1422-1429 (2011)Global signal regression strengthens association between resting-state functional connectivity and behavior., , , , , , , , , and . NeuroImage, (2019)Invariance Principles Allowing of Non-Lyapunov Functions for Estimating Attractor of Discrete Dynamical Systems., , and . IEEE Trans. Automat. Contr., 57 (2): 500-505 (2012)Granger Causality: Its Foundation and Applications in Systems Biology., and . Handbook of Research on Computational and Systems Biology, IGI Global, (2011)Spatial Modeling of Multiple Sclerosis for Disease Subtype Prediction., , , , , and . MICCAI (2), volume 8674 of Lecture Notes in Computer Science, page 797-804. Springer, (2014)Increasing power for voxel-wise genome-wide association studies: The random field theory, least square kernel machines and fast permutation procedures., , , , and . NeuroImage, 63 (2): 858-873 (2012)Componential Granger causality, and its application to identifying the source and mechanisms of the top-down biased activation that controls attention to affective vs sensory processing., , , and . NeuroImage, 59 (2): 1846-1858 (2012)