Enhancing the utility of complex‐valued functional magnetic resonance imaging detection of neurobiological processes through postacquisition estimation and correction of dynamic B0 errors and motion
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[1] L. Heller,et al. Modeling direct effects of neural current on MRI , 2009, Human brain mapping.
[2] Ravi S. Menon. Postacquisition suppression of large‐vessel BOLD signals in high‐resolution fMRI , 2002, Magnetic resonance in medicine.
[3] E C Wong,et al. Processing strategies for time‐course data sets in functional mri of the human brain , 1993, Magnetic resonance in medicine.
[4] Li Sze Chow,et al. Investigation of MR signal modulation due to magnetic fields from neuronal currents in the adult human optic nerve and visual cortex. , 2006, Magnetic resonance imaging.
[5] Peter van Gelderen,et al. Reducing correlated noise in fMRI data , 2008, Magnetic resonance in medicine.
[6] Brent R Logan,et al. An evaluation of spatial thresholding techniques in fMRI analysis , 2008, Human brain mapping.
[7] J. Ibrahim,et al. Regression Models for Identifying Noise Sources in Magnetic Resonance Images , 2009, Journal of the American Statistical Association.
[8] S. Ogawa. Brain magnetic resonance imaging with contrast-dependent oxygenation , 1990 .
[9] J. Durbin,et al. Testing for serial correlation in least squares regression. I. , 1950, Biometrika.
[10] J. Bodurka,et al. Current-induced magnetic resonance phase imaging. , 1999, Journal of magnetic resonance.
[11] R. Bowtell,et al. Initial attempts at directly detecting alpha wave activity in the brain using MRI. , 2004, Magnetic resonance imaging.
[12] T. Breusch. TESTING FOR AUTOCORRELATION IN DYNAMIC LINEAR MODELS , 1978 .
[13] E. J. Hannan. TESTING FOR SERIAL CORRELATION IN LEAST SQUARES REGRESSION , 1957 .
[14] Jeff H. Duyn,et al. Making the most of fMRI at 7 T by suppressing spontaneous signal fluctuations , 2009, NeuroImage.
[15] D. Plenz,et al. Direct magnetic resonance detection of neuronal electrical activity , 2006, Proceedings of the National Academy of Sciences.
[16] M. Stephens. EDF Statistics for Goodness of Fit and Some Comparisons , 1974 .
[17] D. Rowe. Magnitude and phase signal detection in complex‐valued fMRI data , 2009, Magnetic resonance in medicine.
[18] Daniel B. Rowe,et al. A complex way to compute fMRI activation , 2004, NeuroImage.
[19] W. Cleveland,et al. Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting , 1988 .
[20] Luis Hernandez-Garcia,et al. Complex‐valued analysis of arterial spin labeling–based functional magnetic resonance imaging signals , 2009, Magnetic resonance in medicine.
[21] Morteza Shahram,et al. Complex data analysis in high‐resolution SSFP fMRI , 2007, Magnetic resonance in medicine.
[22] W. W. Muir,et al. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity , 1980 .
[23] Vince D. Calhoun,et al. Biophysical modeling of phase changes in BOLD fMRI , 2009, NeuroImage.
[24] S. Shapiro,et al. An Analysis of Variance Test for Normality (Complete Samples) , 1965 .
[25] R. Nowak,et al. Generalized likelihood ratio detection for fMRI using complex data , 1999, IEEE Transactions on Medical Imaging.
[26] Daniel B. Rowe,et al. Parameter estimation in the magnitude-only and complex-valued fMRI data models , 2005, NeuroImage.
[27] Andrew S. Nencka,et al. Reducing the unwanted draining vein BOLD contribution in fMRI with statistical post-processing methods , 2007, NeuroImage.
[28] Daniel B. Rowe,et al. Complex fMRI analysis with unrestricted phase is equivalent to a magnitude-only model , 2005, NeuroImage.
[29] V D Calhoun,et al. Independent component analysis of fMRI data in the complex domain , 2002, Magnetic resonance in medicine.
[30] J. Durbin,et al. Testing for serial correlation in least squares regression. II. , 1950, Biometrika.
[31] Tom Johnstone,et al. Motion correction and the use of motion covariates in multiple‐subject fMRI analysis , 2006, Human brain mapping.
[32] Seong-Gi Kim,et al. Sources of phase changes in BOLD and CBV‐weighted fMRI , 2007, Magnetic resonance in medicine.
[33] R W Cox,et al. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.
[34] G H Glover,et al. Image‐based method for retrospective correction of physiological motion effects in fMRI: RETROICOR , 2000, Magnetic resonance in medicine.
[35] J R Reichenbach,et al. In vivo measurement of changes in venous blood‐oxygenation with high resolution functional MRI at 0.95 Tesla by measuring changes in susceptibility and velocity , 1998, Magnetic resonance in medicine.
[36] J. Bodurka,et al. Direct detection of neuronal activity with MRI: Fantasy, possibility, or reality? , 2005 .
[37] M. Bianciardi,et al. The effect of physiological noise in phase functional magnetic resonance imaging: from blood oxygen level-dependent effects to direct detection of neuronal currents. , 2008, Magnetic resonance imaging.
[38] Daniel B. Rowe,et al. An evaluation of thresholding techniques in fMRI analysis , 2004, NeuroImage.
[39] X. Hu,et al. Simulated phase evolution rewinding (SPHERE): A technique for reducing B0 inhomogeneity effects in MR images , 1997, Magnetic resonance in medicine.
[40] T. W. Anderson,et al. Asymptotic Theory of Certain "Goodness of Fit" Criteria Based on Stochastic Processes , 1952 .
[41] Daniel B. Rowe,et al. Characterizing phase-only fMRI data with an angular regression model , 2007, Journal of Neuroscience Methods.
[42] Daniel B. Rowe. Modeling both the magnitude and phase of complex-valued fMRI data , 2005, NeuroImage.
[43] James S. Hyde,et al. Strategies for block-design fMRI experiments during task-related motion of structures of the oral cavity , 2006, NeuroImage.
[44] Thomas E. Nichols,et al. Diagnosis and exploration of massively univariate neuroimaging models , 2003, NeuroImage.
[45] J. Bodurka,et al. Toward direct mapping of neuronal activity: MRI detection of ultraweak, transient magnetic field changes , 2002 .
[46] L. Godfrey. TESTING AGAINST GENERAL AUTOREGRESSIVE AND MOVING AVERAGE ERROR MODELS WHEN THE REGRESSORS INCLUDE LAGGED DEPENDENT VARIABLES , 1978 .
[47] Andrew S. Nencka,et al. Improving robustness and reliability of phase-sensitive fMRI analysis using temporal off-resonance alignment of single-echo timeseries (TOAST) , 2009, NeuroImage.
[48] D. Tank,et al. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. , 1990, Proceedings of the National Academy of Sciences of the United States of America.
[49] R W Cox,et al. Magnetic field changes in the human brain due to swallowing or speaking , 1998, Magnetic resonance in medicine.