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Dynamic default mode network connectivity diminished in patients with schizophrenia.

, , , , , and . ISBI, page 474-477. IEEE, (2015)

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Application of Graph Theory to Assess Static and Dynamic Brain Connectivity: Approaches for Building Brain Graphs., , , , , , and . Proceedings of the IEEE, 106 (5): 886-906 (2018)Three-way FMRI-DTI-methylation data fusion based on mCCA+jICA and its application to schizophrenia., , , , , , and . EMBC, page 2692-2695. IEEE, (2012)Semi-supervised learning of brain functional networks., , , , and . ISBI, page 1-4. IEEE, (2014)Graph Modularity and Randomness Measures : A Comparative Study., , and . SSIAI, page 33-36. IEEE Computer Society, (2018)Assessing dynamic brain graphs of time-varying connectivity in fMRI data: Application to healthy controls and patients with schizophrenia., , , , , , , , , and 1 other author(s). NeuroImage, (2015)Function-structure associations of the brain: Evidence from multimodal connectivity and covariance studies., , , , and . NeuroImage, (2014)Three-way (N-way) fusion of brain imaging data based on mCCA + jICA and its application to discriminating schizophrenia., , , , , , , , , and 3 other author(s). NeuroImage, (2013)Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data., , , , , , , , , and 2 other author(s). NeuroImage, (2017)Abnormal Dynamic Functional Network Connectivity and Graph Theoretical Analysis in Major Depressive Disorder., , , , , , , , , and 4 other author(s). EMBC, page 558-561. IEEE, (2018)A group ICA based framework for evaluating resting fMRI markers when disease categories are unclear: application to schizophrenia, bipolar, and schizoaffective disorders., , , , , , , and . NeuroImage, (2015)