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Multimodal and Multi-Tissue Measures of Connectivity Revealed by Joint Independent Component Analysis.

, , , , , , and . J. Sel. Topics Signal Processing, 2 (6): 986-997 (2008)

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Introduction to the Issue on fMRI Analysis for Human Brain Mapping., , , , , , and . J. Sel. Topics Signal Processing, 2 (6): 813-816 (2008)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)Using joint ICA to link function and structure using MEG and DTI in schizophrenia., , , , , and . NeuroImage, (2013)A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function., , and . IEEE Signal Process. Lett., (2008)Hybrid ICA-Bayesian network approach reveals distinct effective connectivity differences in schizophrenia., , , , , and . NeuroImage, 42 (4): 1560-1568 (2008)Multimodal and Multi-Tissue Measures of Connectivity Revealed by Joint Independent Component Analysis., , , , , , and . J. Sel. Topics Signal Processing, 2 (6): 986-997 (2008)Efficient Multiplicative Updates for Support Vector Machines., , , , and . SDM, page 1220-1231. SIAM, (2009)Sparse representation based biomarker selection for schizophrenia with integrated analysis of fMRI and SNP data., , , , and . ISBI, page 756-759. IEEE, (2013)Canonical Correlation Analysis for Feature-Based Fusion of Biomedical Imaging Modalities and Its Application to Detection of Associative Networks in Schizophrenia., , , and . J. Sel. Topics Signal Processing, 2 (6): 998-1007 (2008)Transient increased thalamic-sensory connectivity and decreased whole-brain dynamism in autism., , , , , , , , and . NeuroImage, (2019)