Sensitivity enhancement of task-evoked fMRI using ensemble empirical mode decomposition
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Changwei W. Wu | Pei-Jung Tsai | Ai-Ling Hsu | Geng-Hong Lin | Shang-Hua N. Lin | Ching-Po Lin | M. Lo | A. Yang | Geng-Hong Lin | Ai-Ling Hsu | Pei-Jung Tsai
[1] E. DeYoe,et al. Reduction of physiological fluctuations in fMRI using digital filters , 1996, Magnetic resonance in medicine.
[2] S. Rombouts,et al. Consistent resting-state networks across healthy subjects , 2006, Proceedings of the National Academy of Sciences.
[3] Norden E. Huang,et al. Ensemble Empirical Mode Decomposition: a Noise-Assisted Data Analysis Method , 2009, Adv. Data Sci. Adapt. Anal..
[4] Gabriel Rilling,et al. Detrending and denoising with empirical mode decompositions , 2004, 2004 12th European Signal Processing Conference.
[5] Changwei W. Wu,et al. Variations in BOLD response latency estimated from event‐related fMRI at 3T: Comparisons between gradient‐echo and Spin‐echo , 2013, Int. J. Imaging Syst. Technol..
[6] S. S. Shen,et al. A confidence limit for the empirical mode decomposition and Hilbert spectral analysis , 2003, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.
[7] B. Biswal,et al. Functional connectivity in the motor cortex of resting human brain using echo‐planar mri , 1995, Magnetic resonance in medicine.
[8] Rupesh Kumar,et al. Local Properties of Vigilance States: EMD Analysis of EEG Signals during Sleep-Waking States of Freely Moving Rats , 2013, PloS one.
[9] Abraham Z. Snyder,et al. A method for using blocked and event-related fMRI data to study “resting state” functional connectivity , 2007, NeuroImage.
[10] N. Huang,et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.
[11] Andrea Bergmann,et al. Statistical Parametric Mapping The Analysis Of Functional Brain Images , 2016 .
[12] Thomas T. Liu,et al. Analysis and Design of Perfusion-Based Event-Related fMRI Experiments , 2002, NeuroImage.
[13] Richard A. Harshman,et al. Noise Reduction in BOLD-Based fMRI Using Component Analysis , 2002, NeuroImage.
[14] Justin L. Vincent,et al. Intrinsic functional architecture in the anaesthetized monkey brain , 2007, Nature.
[15] Rui Zhang,et al. Multivariate empirical mode decomposition based sub-frequency bands analysis of the default mode network: a resting-state fMRI data study , 2015, Applied Informatics.
[16] Mark J. Lowe,et al. Isolating physiologic noise sources with independently determined spatial measures , 2007, NeuroImage.
[17] Peter Bandettini,et al. Functional MRI today. , 2007, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.
[18] N. Logothetis,et al. Neurophysiological investigation of the basis of the fMRI signal , 2001, Nature.
[19] Marcus E. Raichle,et al. The Restless Brain , 2011, Brain Connect..
[20] Zhaohua Wu,et al. On the trend, detrending, and variability of nonlinear and nonstationary time series , 2007, Proceedings of the National Academy of Sciences.
[21] Aapo Hyvärinen,et al. Independent component analysis of nondeterministic fMRI signal sources , 2003, NeuroImage.
[22] Norden E. Huang,et al. On the time-varying trend in global-mean surface temperature , 2011 .
[23] Gabriel Rilling,et al. Empirical mode decomposition as a filter bank , 2004, IEEE Signal Processing Letters.
[24] V. Haughton,et al. Frequencies contributing to functional connectivity in the cerebral cortex in "resting-state" data. , 2001, AJNR. American journal of neuroradiology.
[25] Yi Zhang,et al. Frequency Specificity of Regional Homogeneity in the Resting-State Human Brain , 2014, PloS one.
[26] Arno Villringer,et al. Resting developments: a review of fMRI post-processing methodologies for spontaneous brain activity , 2010, Magnetic Resonance Materials in Physics, Biology and Medicine.
[27] G Carrault,et al. Denoising preterm EEG by signal decomposition and adaptive filtering: a comparative study. , 2015, Medical engineering & physics.
[28] Habib Benali,et al. CORSICA: correction of structured noise in fMRI by automatic identification of ICA components. , 2007, Magnetic resonance imaging.
[29] Jinglei Lv,et al. FMRI Signal Analysis Using Empirical Mean Curve Decomposition , 2013, IEEE Transactions on Biomedical Engineering.
[30] T. Sejnowski,et al. Human Brain Mapping 6:368–372(1998) � Independent Component Analysis of fMRI Data: Examining the Assumptions , 2022 .
[31] Catie Chang,et al. Time–frequency dynamics of resting-state brain connectivity measured with fMRI , 2010, NeuroImage.
[32] Takashi Hanakawa,et al. Spontaneous Slow Fluctuation of EEG Alpha Rhythm Reflects Activity in Deep-Brain Structures: A Simultaneous EEG-fMRI Study , 2013, PloS one.
[33] Hualou Liang,et al. Empirical mode decomposition of field potentials from macaque V4 in visual spatial attention , 2005, Biological Cybernetics.
[34] Ravi S. Menon,et al. Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. , 1992, Proceedings of the National Academy of Sciences of the United States of America.
[35] Kang-Ming Chang,et al. Gaussian Noise Filtering from ECG by Wiener Filter and Ensemble Empirical Mode Decomposition , 2011, J. Signal Process. Syst..
[36] N. Huang,et al. A study of the characteristics of white noise using the empirical mode decomposition method , 2004, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.
[37] G. Northoff,et al. Rest-stimulus interaction in the brain: a review , 2010, Trends in Neurosciences.
[38] Men-Tzung Lo,et al. Nonlinear phase interaction between nonstationary signals: a comparison study of methods based on Hilbert-Huang and Fourier transforms. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[39] Fulei Chu,et al. Recent advances in time–frequency analysis methods for machinery fault diagnosis: A review with application examples , 2013 .
[40] Suzanne T. Witt,et al. Functional neuroimaging correlates of finger-tapping task variations: An ALE meta-analysis , 2008, NeuroImage.
[41] Sabine Van Huffel,et al. Source Separation From Single-Channel Recordings by Combining Empirical-Mode Decomposition and Independent Component Analysis , 2010, IEEE Transactions on Biomedical Engineering.
[42] Norihiro Sadato,et al. Removing the effects of task-related motion using independent-component analysis , 2005, NeuroImage.
[43] G H Glover,et al. Image‐based method for retrospective correction of physiological motion effects in fMRI: RETROICOR , 2000, Magnetic resonance in medicine.
[44] Seán F. McLoone,et al. The Use of Ensemble Empirical Mode Decomposition With Canonical Correlation Analysis as a Novel Artifact Removal Technique , 2013, IEEE Transactions on Biomedical Engineering.
[45] Stephen M Smith,et al. Correspondence of the brain's functional architecture during activation and rest , 2009, Proceedings of the National Academy of Sciences.
[46] Norden E. Huang,et al. On the Filtering Properties of the Empirical Mode Decomposition , 2010, Adv. Data Sci. Adapt. Anal..
[47] V. Haughton,et al. Mapping functionally related regions of brain with functional connectivity MR imaging. , 2000, AJNR. American journal of neuroradiology.
[48] N. Huang,et al. A new view of nonlinear water waves: the Hilbert spectrum , 1999 .
[49] Rainer Hammwöhner,et al. Ensemble Empirical Mode Decomposition Analysis of EEG Data Collected during a Contour Integration Task , 2015, PloS one.
[50] Tianzi Jiang,et al. A novel approach to activation detection in fMRI based on empirical mode decomposition. , 2010, Journal of integrative neuroscience.
[51] V. Calhoun,et al. Modulation of temporally coherent brain networks estimated using ICA at rest and during cognitive tasks , 2008, Human brain mapping.
[52] Yung-Hung Wang,et al. On the computational complexity of the empirical mode decomposition algorithm , 2014 .
[53] K Murphy,et al. fMRI in the presence of task-correlated breathing changes , 2009, NeuroImage.
[54] L. K. Hansen,et al. Independent component analysis of functional MRI: what is signal and what is noise? , 2003, Current Opinion in Neurobiology.