Spatiotemporal Empirical Mode Decomposition of Resting-State fMRI Signals: Application to Global Signal Regression.

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作者： Narges,Moradi ^[1] ; Mehdy,Dousty ^[2] ; Roberto C,Sotero ^[3]

作者单位： Biomedical Engineering Graduate Program, University of Calgary, Calgary, AB, Canada. ^[1] Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada. ^[2] Computational Neurophysics Lab, Department of Radiology, University of Calgary, Calgary, AB, Canada. ^[3] Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada. ^[4] KITE, Toronto Rehab, University Health Network, Toronto, ON, Canada. ^[5]

关键词 empirical mode decomposition fMRI global Signal low-pass filtering resting-state functional connectivity MRI spatial intrinsic mode function temporal intrinsic mode function

DOI 10.3389/fnins.2019.00736

PMID 31396032

发布时间 2020-10-01

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Frontiers in neuroscience

2019年13卷

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Spatiotemporal Empirical Mode Decomposition of Resting-State fMRI Signals: Application to Global Signal Regression.

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Spatiotemporal Empirical Mode Decomposition of Resting-State fMRI Signals: Application to Global Signal Regression.

Frontiers in neuroscience

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