The Quantitative Evaluation of Functional Neuroimaging Experiments: The NPAIRS Data Analysis Framework
暂无分享,去创建一个
Lars Kai Hansen | Jon Anderson | Stephen C. Strother | Ulrik Kjems | David Rottenberg | L. K. Hansen | S. Strother | Jon R. Anderson | U. Kjems | R. Kustra | J. Sidtis | S. Frutiger | S. Muley | S. LaConte | D. Rottenberg
[1] R. Tibshirani,et al. Penalized Discriminant Analysis , 1995 .
[2] Shizuhiko Nishisato,et al. Elements of Dual Scaling: An Introduction To Practical Data Analysis , 1993 .
[3] D. A. Rottenberg,et al. PET Studies of Perceptuomotor Learning in a Mirror-reversal Paradigm , 1998, NeuroImage.
[4] Lars Kai Hansen,et al. Evaluating preprocessing choices in single-subject BOLD-fMRI studies using data-driven performance metrics , 2001, NeuroImage.
[5] Alan C. Evans,et al. Detecting changes in nonisotropic images , 1999, Human brain mapping.
[6] Dimitris N. Politis,et al. Computer-intensive methods in statistical analysis , 1998, IEEE Signal Process. Mag..
[7] V. Dhawan,et al. Reproducibility of regional metabolic covariance patterns: comparison of four populations. , 1999, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[8] F. Å. Nielsen,et al. Canonical Ridge Analysis with Ridge Parameter Optimization , 1998, NeuroImage.
[9] E. Bullmore,et al. Functional Magnetic Resonance Image Analysis of a Large-Scale Neurocognitive Network , 1996, NeuroImage.
[10] J Xiong,et al. Assessment and optimization of functional MRI analyses , 1996, Human brain mapping.
[11] Daniel S. O'Leary,et al. Factors That Influence Effect Size in15O PET Studies: A Meta-analytic Review , 1997, NeuroImage.
[12] Karl J. Friston,et al. Is Multivariate Analysis of PET Data More Revealing Than the Univariate Approach? Evidence from a Study of Episodic Memory Retrieval , 1996, NeuroImage.
[13] R. Tibshirani,et al. An Introduction to the Bootstrap , 1995 .
[14] Brian D. Ripley,et al. Pattern Recognition and Neural Networks , 1996 .
[15] S. C. Strother,et al. Multidimensional state-spaces for fMRI and PET activation studies , 1996, NeuroImage.
[16] S C Strother,et al. Comparison of voxel- and volume-of-interest-based analyses in FDG PET scans of HIV positive and healthy individuals. , 2000, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[17] Richard E. Carson,et al. Noise characteristics of 3-D and 2-D PET images , 1998, IEEE Transactions on Medical Imaging.
[18] Thomas E. Nichols,et al. Statistical limitations in functional neuroimaging. II. Signal detection and statistical inference. , 1999, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[19] Stephen C. Strother,et al. Penalized Discriminant Analysis of [15O]-water PET Brain Images with Prediction Error Selection of Smoothness and Regularization , 2001, IEEE Trans. Medical Imaging.
[20] Rafal Kustra,et al. Statistical analysis of medical images with applications to neuroimaging , 2000 .
[21] Lars Kai Hansen,et al. Measuring Activation Pattern Reproducibility Using Resampling Techniques , 1998 .
[22] N C Andreasen,et al. Tests for Comparing Images Based on Randomization and Permutation Methods , 1996, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[23] S C Strother,et al. Abnormal cerebral glucose metabolism in HIV-1 seropositive subjects with and without dementia. , 1996, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[24] John C. Gore,et al. ROC Analysis of Statistical Methods Used in Functional MRI: Individual Subjects , 1999, NeuroImage.
[25] S. Strother,et al. Reproducibility of BOLD‐based functional MRI obtained at 4 T , 1999, Human brain mapping.
[26] Tom Heskes,et al. Bias/Variance Decompositions for Likelihood-Based Estimators , 1998, Neural Computation.
[27] Gary F. Egan,et al. Abnormal Functional Connectivity in Posttraumatic Stress Disorder , 2002, NeuroImage.
[28] B. Ripley. Statistical theories of model fitting , 1998 .
[29] Jan Larsen,et al. On optimal data split for generalization estimation and model selection , 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).
[30] Karl J. Friston,et al. A unified statistical approach for determining significant signals in images of cerebral activation , 1996, Human brain mapping.
[31] S. C. Strother,et al. Generalization performance of nonlinear vs. Linear models for [15O]water PET functional activation studies , 1996, NeuroImage.
[32] F Makedon,et al. Statistical Methods in Medical Research Data Mining in Brain Imaging , 2022 .
[33] Karl J. Friston,et al. Statistical parametric maps in functional imaging: A general linear approach , 1994 .
[34] Vic Barnett,et al. Outliers in Statistical Data , 1980 .
[35] M. Hayden,et al. The FDG/PET Methodology for Early Detection of Disease Onset: A Statistical Model , 1991, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[36] Lars Kai Hansen,et al. Modeling the hemodynamic response in fMRI using smooth FIR filters , 2000, IEEE Transactions on Medical Imaging.
[37] Jerome H. Friedman,et al. An Overview of Predictive Learning and Function Approximation , 1994 .
[38] J. V. Haxby,et al. Spatial Pattern Analysis of Functional Brain Images Using Partial Least Squares , 1996, NeuroImage.
[39] L. K. Hansen,et al. Generalization: The Hidden Agenda of Learning , 1997, IEEE Signal Process. Mag..
[40] P. Pietrini,et al. Early Detection of Alzheimer's Disease: A Statistical Approach Using Positron Emission Tomographic Data , 1993, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[41] B. Efron. The jackknife, the bootstrap, and other resampling plans , 1987 .
[42] Karl J. Friston,et al. Multisubject fMRI Studies and Conjunction Analyses , 1999, NeuroImage.
[43] R. Turner,et al. Characterizing Dynamic Brain Responses with fMRI: A Multivariate Approach , 1995, NeuroImage.
[44] Shing-Chung Ngan,et al. Temporal Filtering of Event-Related fMRI Data Using Cross-Validation , 2000, NeuroImage.
[45] S. Petersen,et al. The effects of practice on the functional anatomy of task performance. , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[46] R. Tibshirani,et al. Improvements on Cross-Validation: The 632+ Bootstrap Method , 1997 .
[47] Stephen C. Strother,et al. Multivariate Predictive Relationship between Kinematic and Functional Activation Patterns in a PET Study of Visuomotor Learning , 2000, NeuroImage.
[48] E. Bullmore,et al. How Good Is Good Enough in Path Analysis of fMRI Data? , 2000, NeuroImage.
[49] Iwao Kanno,et al. On the Detection of Activation Patterns Using Principal Components Analysis , 1998 .
[50] J D Watson,et al. Nonparametric Analysis of Statistic Images from Functional Mapping Experiments , 1996, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[51] Stephen C. Strother,et al. Are Brain Functions Really Additive? , 1996, NeuroImage.
[52] L. K. Hansen,et al. Generalizable Patterns in Neuroimaging: How Many Principal Components? , 1999, NeuroImage.
[53] Claus Svarer,et al. Cluster analysis of activity‐time series in motor learning , 2002, Human brain mapping.
[54] L. K. Hansen,et al. Activation pattern reproducibility: Measuring the effects of group size and data analysis models , 1997, Human brain mapping.
[55] Karl J. Friston,et al. Characterizing the Response of PET and fMRI Data Using Multivariate Linear Models , 1997, NeuroImage.
[56] M. Stone. Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .
[57] P. Good,et al. Permutation Tests: A Practical Guide to Resampling Methods for Testing Hypotheses , 1995 .
[58] Lars Kai Hansen,et al. Consensus Inference in Neuroimaging , 2001, NeuroImage.
[59] Lars Kai Hansen,et al. Neural Network Ensembles , 1990, IEEE Trans. Pattern Anal. Mach. Intell..
[60] J. Mazziotta,et al. Automated image registration , 1993 .
[61] S C Strother,et al. Commentary and Opinion: I. Principal Component Analysis, Variance Partitioning, and “Functional Connectivity” , 1995, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[62] M. N. Rajah,et al. Interactions of prefrontal cortex in relation to awareness in sensory learning. , 1999, Science.
[63] J R Moeller,et al. A Regional Covariance Approach to the Analysis of Functional Patterns in Positron Emission Tomographic Data , 1991, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[64] B J Biggerstaff,et al. Incorporating variability in estimates of heterogeneity in the random effects model in meta-analysis. , 1997, Statistics in medicine.
[65] Vladimir Cherkassky,et al. Learning from Data: Concepts, Theory, and Methods , 1998 .
[66] R. Woods,et al. Principal Component Analysis and the Scaled Subprofile Model Compared to Intersubject Averaging and Statistical Parametric Mapping: I. “Functional Connectivity” of the Human Motor System Studied with [15O]Water PET , 1995, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[67] Stephen C. Strother,et al. Effects of Changes in Experimental Design on PET Studies of Isometric Force , 2001, NeuroImage.
[68] Lars Kai Hansen,et al. Nonlinear versus Linear Models in Functional Neuroimaging: Learning Curves and Generalization Crossover , 1997, IPMI.
[69] Karen Faith Berman,et al. Mapping Voxel-Based Statistical Power on Parametric Images , 1998, NeuroImage.
[70] Scott T. Grafton,et al. Automated image registration: I. General methods and intrasubject, intramodality validation. , 1998, Journal of computer assisted tomography.
[71] Athanasios Papoulis,et al. Probability, Random Variables and Stochastic Processes , 1965 .
[72] S. Strother,et al. Quantitative Comparisons of Image Registration Techniques Based on High‐Resolution MRI of the Brain , 1994, Journal of computer assisted tomography.
[73] M. McKeown. Detection of Consistently Task-Related Activations in fMRI Data with Hybrid Independent Component Analysis , 2000, NeuroImage.
[74] L. K. Hansen,et al. Plurality and Resemblance in fMRI Data Analysis , 1999, NeuroImage.
[75] Thomas E. Nichols,et al. Statistical limitations in functional neuroimaging. I. Non-inferential methods and statistical models. , 1999, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[76] Karl J. Friston,et al. A multivariate analysis of PET activation studies , 1996, Human brain mapping.
[77] Joe Whittaker,et al. Application of the Parametric Bootstrap to Models that Incorporate a Singular Value Decomposition , 1995 .