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A study of spatial variation in fMRI brain networks via independent vector analysis: Application to schizophrenia.

, , , , , and . PRNI, page 1-4. IEEE, (2014)

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Characterization of connectivity dynamics in intrinsic brain networks., , , and . GlobalSIP, page 831-834. IEEE, (2013)Classification of schizophrenia and bipolar patients using static and time-varying resting-state FMRI brain connectivity., , , , , , and . ISBI, page 251-254. IEEE, (2015)A framework for linking resting-state chronnectome/genome features in schizophrenia: A pilot study., , , , , , , , , and 9 other author(s). NeuroImage, (2019)Replicability of time-varying connectivity patterns in large resting state fMRI samples., , , , , , and . NeuroImage, (2017)Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications., , , , , , , , , and 2 other author(s). CoRR, (2018)A Method for Intertemporal Functional-Domain Connectivity Analysis: Application to Schizophrenia Reveals Distorted Directional Information Flow., , , and . IEEE Trans. Biomed. Engineering, 63 (12): 2525-2539 (2016)Higher dimensional fMRI connectivity dynamics show reduced dynamism in schizophrenia patients., , , and . PRNI, page 1-4. IEEE, (2014)Time-varying frequency modes of resting fMRI brain networks reveal significant gender differences., , , and . ICASSP, page 6310-6314. IEEE, (2016)Mutually temporally independent connectivity patterns: A new framework to study the dynamics of brain connectivity at rest with application to explain group difference based on gender., , and . NeuroImage, (2015)Whole-brain connectivity dynamics reflect both task-specific and individual-specific modulation: A multitask study., , , , , , and . NeuroImage, 180 (Part): 495-504 (2018)