Increased sensitivity in neuroimaging analyses using robust regression

[1]  Michael H. Kutner Applied Linear Statistical Models , 1974 .

[2]  V. Barnett,et al.  Applied Linear Statistical Models , 1975 .

[3]  P. Holland,et al.  Robust regression using iteratively reweighted least-squares , 1977 .

[4]  Frederick Mosteller,et al.  Exploring Data Tables, Trends and Shapes. , 1986 .

[5]  D. Ruppert,et al.  A Note on Computing Robust Regression Estimates via Iteratively Reweighted Least Squares , 1988 .

[6]  William Dumouchel,et al.  Integrating a robust option into a multiple regression computing environment , 1992 .

[7]  R. Buxton,et al.  Pulsatile flow artifacts in 3D magnetic resonance imaging , 1993, Magnetic resonance in medicine.

[8]  Karl J. Friston,et al.  Analysis of fMRI Time-Series Revisited , 1995, NeuroImage.

[9]  Karl J. Friston,et al.  Analysis of fMRI Time-Series Revisited—Again , 1995, NeuroImage.

[10]  R. Turner,et al.  Characterizing Evoked Hemodynamics with fMRI , 1995, NeuroImage.

[11]  J. Cohen,et al.  Spiral K‐space MR imaging of cortical activation , 1995, Journal of magnetic resonance imaging : JMRI.

[12]  X Hu,et al.  Retrospective estimation and correction of physiological artifacts in fMRI by direct extraction of physiological activity from MR data , 1996, Magnetic resonance in medicine.

[13]  David L. Woodruff,et al.  Identification of Outliers in Multivariate Data , 1996 .

[14]  K W Langenberger,et al.  Nonlinear motion artifact reduction in event-triggered gradient-echo FMRI. , 1997, Magnetic resonance imaging.

[15]  M. Raichle,et al.  Anatomic Localization and Quantitative Analysis of Gradient Refocused Echo-Planar fMRI Susceptibility Artifacts , 1997, NeuroImage.

[16]  J. Lewin,et al.  Inadequacy of motion correction algorithms in functional MRI: Role of susceptibility‐induced artifacts , 1997, Journal of magnetic resonance imaging : JMRI.

[17]  Karl J. Friston,et al.  Characterizing the Response of PET and fMRI Data Using Multivariate Linear Models , 1997, NeuroImage.

[18]  C. L. Kwan,et al.  Event‐related fMRI of pain: entering a new era in imaging pain , 1998, Neuroreport.

[19]  S Makeig,et al.  Analysis of fMRI data by blind separation into independent spatial components , 1998, Human brain mapping.

[20]  J. Ashburner,et al.  Nonlinear spatial normalization using basis functions , 1999, Human brain mapping.

[21]  K J Friston,et al.  The predictive value of changes in effective connectivity for human learning. , 1999, Science.

[22]  Ravi S. Menon,et al.  Dissociating pain from its anticipation in the human brain. , 1999, Science.

[23]  G. Glover,et al.  Physiological noise in oxygenation‐sensitive magnetic resonance imaging , 2001, Magnetic resonance in medicine.

[24]  U. Habel,et al.  Subjective Ratings of Pain Correlate with Subcortical-Limbic Blood Flow: An fMRI Study , 2001, Neuropsychobiology.

[25]  G L Shulman,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:A default mode of brain function , 2001 .

[26]  J Mazziotta,et al.  A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[27]  M. Hubert Multivariate outlier detection and robust covariance matrix estimation - Discussion , 2001 .

[28]  H. Breiter,et al.  Reward Circuitry Activation by Noxious Thermal Stimuli , 2001, Neuron.

[29]  R. Buxton,et al.  Estimation of respiration‐induced noise fluctuations from undersampled multislice fMRI data † , 2001, Magnetic resonance in medicine.

[30]  Francisco J. Prieto,et al.  Multivariate Outlier Detection and Robust Covariance Matrix Estimation , 2001, Technometrics.

[31]  M. Raichle,et al.  Searching for a baseline: Functional imaging and the resting human brain , 2001, Nature Reviews Neuroscience.

[32]  C. Jack,et al.  Real‐time autoshimming for echo planar timecourse imaging , 2002, Magnetic resonance in medicine.

[33]  Robert Turner,et al.  Image Distortion Correction in fMRI: A Quantitative Evaluation , 2002, NeuroImage.

[34]  Roland Peyron,et al.  Role of Operculoinsular Cortices in Human Pain Processing: Converging Evidence from PET, fMRI, Dipole Modeling, and Intracerebral Recordings of Evoked Potentials , 2002, NeuroImage.

[35]  G. Pagnoni,et al.  Does Anticipation of Pain Affect Cortical Nociceptive Systems? , 2002, The Journal of Neuroscience.

[36]  M. Hubert,et al.  A fast method for robust principal components with applications to chemometrics , 2002 .

[37]  Stephen M. Smith,et al.  Accurate, Robust, and Automated Longitudinal and Cross-Sectional Brain Change Analysis , 2002, NeuroImage.

[38]  L. J. Hardies,et al.  An Optimized Individual Target Brain in the Talairach Coordinate System , 2002, NeuroImage.

[39]  M. Hubert,et al.  A robust PCR method for high‐dimensional regressors , 2003 .

[40]  Thomas E. Nichols,et al.  Nonparametric permutation tests for functional neuroimaging: A primer with examples , 2002, Human brain mapping.

[41]  A. Toga,et al.  New approaches in brain morphometry. , 2002, The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry.

[42]  S. Kapur,et al.  Direct Activation of the Ventral Striatum in Anticipation of Aversive Stimuli , 2003, Neuron.

[43]  Thomas E. Nichols,et al.  Diagnosis and exploration of massively univariate neuroimaging models , 2003, NeuroImage.

[44]  M. Hubert,et al.  Robust methods for partial least squares regression , 2003 .

[45]  L. K. Hansen,et al.  Independent component analysis of functional MRI: what is signal and what is noise? , 2003, Current Opinion in Neurobiology.

[46]  Jean-Baptiste Poline,et al.  Unsupervised robust nonparametric estimation of the hemodynamic response function for any fMRI experiment , 2003, IEEE Transactions on Medical Imaging.

[47]  Guinevere F. Eden,et al.  Multivariate analysis of neuronal interactions in the generalized partial least squares framework: simulations and empirical studies , 2003, NeuroImage.

[48]  Scott J Peltier,et al.  Detecting low‐frequency functional connectivity in fMRI using a self‐organizing map (SOM) algorithm , 2003, Human brain mapping.

[49]  Thomas E. Nichols,et al.  Nonstationary cluster-size inference with random field and permutation methods , 2004, NeuroImage.

[50]  Mark W. Woolrich,et al.  Fully Bayesian spatio-temporal modeling of FMRI data , 2004, IEEE Transactions on Medical Imaging.

[51]  B. Ripley,et al.  Robust Statistics , 2018, Encyclopedia of Mathematical Geosciences.

[52]  J. Teugels,et al.  Encyclopedia of actuarial science , 2004 .

[53]  Sabine Himmel,et al.  Exploring Data Tables, Trends, and Shapes , 2007 .