Spatiotemporal Empirical Mode Decomposition of Resting-State fMRI Signals: Application to Global Signal Regression
Resting-state functional connectivity MRI (rs-fcMRI) is a common method for mapping functional brain networks. However, estimation of these networks is affected by the presence of a common global systemic noise, or global signal (GS). Previous studies have shown that the common preprocessing steps o...
Main Authors: | Narges Moradi, Mehdy Dousty, Roberto C. Sotero |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2019-07-01
|
Series: | Frontiers in Neuroscience |
Subjects: | |
Online Access: | https://www.frontiersin.org/article/10.3389/fnins.2019.00736/full |
Similar Items
-
Energy-Period Profiles of Brain Networks in Group fMRI Resting-State Data: A Comparison of Empirical Mode Decomposition With the Short-Time Fourier Transform and the Discrete Wavelet Transform
by: Dietmar Cordes, et al.
Published: (2021-05-01) -
Pressure fluctuation signal analysis of pump based on ensemble empirical mode decomposition method
by: Hong Pan, et al.
Published: (2014-04-01) -
Frequency Domain Based Approach for Denoising of Underwater Acoustic Signal Using EMD
by: Veeraiyan Vijayabaskar, et al.
Published: (2013-03-01) -
Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition
by: Fu-Tai Wang, et al.
Published: (2015-07-01) -
DAMAGE IDENTIFICATION IN A MULTILEVEL STRUCTURE USING EMPIRICAL MODE DECOMPOSITION
by: D. MALLIKARJUNA REDDY, et al.
Published: (2017-12-01)