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Adaptive window selection in estimating dynamic functional connectivity of resting-state fMRI.

, , , , , , and . ICICS, page 1-4. IEEE, (2013)

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Functional MRI as a Tool to Quantify Cortical Changes from Vision Rehabilitation., , , , , , and . ICTAI, page 762-765. IEEE Computer Society, (2009)Automatic Recognition of Resting State fMRI Networks with Dictionary Learning., , , and . BI, volume 11309 of Lecture Notes in Computer Science, page 249-259. Springer, (2018)How Many FMRI Scans are Necessary and Sufficient for Resting Brain Connectivity Analysis?, , , and . GlobalSIP, page 494-498. IEEE, (2018)Functional Covariance Networks: Obtaining Resting-State Networks from Intersubject Variability., , , , and . Brain Connect., 2 (4): 203-217 (2012)Spatial sparsification and low rank projection for fast analysis of multi-subject resting state fMRI data., , , and . ISBI, page 1280-1283. IEEE, (2018)Predicting individual decision-making responses based on single-trial EEG., , , , , , , , , and 1 other author(s). NeuroImage, (2020)Mapping the functional connectivity of anterior cingulate cortex., , , , , and . NeuroImage, 37 (2): 579-588 (2007)Interhemispheric neuroplasticity following limb deafferentation detected by resting-state functional connectivity magnetic resonance imaging (fcMRI) and functional magnetic resonance imaging (fMRI)., , , , , , , and . NeuroImage, 49 (3): 2467-2478 (2010)Time-varying correlation coefficients estimation and its application to dynamic connectivity analysis of fMRI., , , , , and . EMBC, page 2944-2947. IEEE, (2013)Decomposition of Vergence Dynamics Using Independent Component Analysis., , , , , and . ICTAI, page 766-770. IEEE Computer Society, (2009)