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Discriminating schizophrenia and bipolar disorder by fusing fMRI and DTI in a multimodal CCA+ joint ICA model., , , , , , , and . NeuroImage, 57 (3): 839-855 (2011)Multimodal and Multi-Tissue Measures of Connectivity Revealed by Joint Independent Component Analysis., , , , , , and . IEEE J. Sel. Top. Signal Process., 2 (6): 986-997 (2008)Extracting principle components for discriminant analysis of FMRI images., , , and . ICASSP, page 449-452. IEEE, (2008)Changes in fMRI magnitude data and phase data observed in block-design and event-related tasks., , , , , , and . NeuroImage, 49 (4): 3149-3160 (2010)Application of principal component analysis to distinguish patients with schizophrenia from healthy controls based on fractional anisotropy measurements., , and . NeuroImage, 42 (2): 675-682 (2008)Characterization of a normal control group: Are they healthy?, , , , , , , , and . NeuroImage, (2014)An approach to directly link ICA and seed-based functional connectivity: Application to schizophrenia., , , , and . NeuroImage, (2018)Sex differences in the relationship between white matter connectivity and creativity., , , , , , , , and . NeuroImage, (2014)On the Extraction of Pattern Features from Continuous Measurements., and . IEEE Trans. Syst. Sci. Cybern., 6 (2): 110-115 (1970)Tracking spatial dynamics of functional connectivity during a task., , and . NeuroImage, (2021)