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Whole-brain connectivity dynamics reflect both task-specific and individual-specific modulation: A multitask study.

, , , , , , and . NeuroImage, 180 (Part): 495-504 (2018)

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Classification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivity., , , , , , and . NeuroImage, (2016)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)A study of spatial variation in fMRI brain networks via independent vector analysis: Application to schizophrenia., , , , , and . PRNI, page 1-4. IEEE, (2014)Mapping and interpreting the dynamic connectivity of the brain., , , and . NeuroImage, 180 (Part): 335-336 (2018)Dynamic coherence analysis of resting fMRI data to jointly capture state-based phase, frequency, and time-domain information., , , and . NeuroImage, (2015)Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder., , , , , , , , , and 4 other author(s). Brain Connect., 11 (10): 838-849 (2021)Low-Rank Learning by Design: the Role of Network Architecture and Activation Linearity in Gradient Rank Collapse., , , , and . CoRR, (2024)An Unsupervised Feature Learning Approach for Elucidating Hidden Dynamics in rs-fMRI Functional Network Connectivity., , , and . EMBC, page 4449-4452. IEEE, (2022)Multiframe Evolving Dynamic Functional Network Connectivity Motifs (Evodfncs) from Continuity-Preserving Planar Embedding., , and . EMBC, page 3066-3069. IEEE, (2021)A Novel Activation Maximization-based Approach for Insight into Electrophysiology Classifiers., , , and . BIBM, page 3358-3365. IEEE, (2021)