Some Novel Spatial Stochastic Models for Functional Neuroimaging Analysis.
暂无分享,去创建一个
[1] C. Preston. Spatial birth and death processes , 1975, Advances in Applied Probability.
[2] Bernard W. Silverman,et al. Methods for Analysing Spatial Processes of Several Types of Points , 1982 .
[3] S. Ogawa,et al. Oxygenation‐sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields , 1990, Magnetic resonance in medicine.
[4] Anders M. Dale,et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.
[5] Thomas E. Nichols,et al. Thresholding of Statistical Maps in Functional Neuroimaging Using the False Discovery Rate , 2002, NeuroImage.
[6] Jack L. Lancaster,et al. CBF changes during brain activation: fMRI vs. PET , 2004, NeuroImage.
[7] Thomas E. Nichols,et al. Controlling the familywise error rate in functional neuroimaging: a comparative review , 2003, Statistical methods in medical research.
[8] J L Lancaster,et al. Functional volumes modeling: Theory and preliminary assessment , 1997, Human brain mapping.
[9] K. Zilles,et al. Coordinate‐based activation likelihood estimation meta‐analysis of neuroimaging data: A random‐effects approach based on empirical estimates of spatial uncertainty , 2009, Human brain mapping.
[10] Tor D Wager,et al. Neuroimaging studies of shifting attention: a meta-analysis , 2004, NeuroImage.
[11] Adrian Baddeley,et al. Multivariate and marked point processes , 2010 .
[12] R. Waagepetersen,et al. Modern Statistics for Spatial Point Processes * , 2007 .
[13] J. Raduà,et al. Voxel-wise meta-analysis of grey matter changes in obsessive-compulsive disorder. , 2009, The British journal of psychiatry : the journal of mental science.
[14] A. Baddeley,et al. Non‐ and semi‐parametric estimation of interaction in inhomogeneous point patterns , 2000 .
[15] C. Patlak,et al. Principles of Susceptibility Contrast-Based Functional MRI: The Sign of the Functional MRI Response , 2000 .
[16] Nicola G. Best,et al. Modeling the Impact of Traffic-Related Air Pollution on Childhood Respiratory Illness , 2002 .
[17] R. Wolpert,et al. Spatial Inference of Nitrate Concentrations in Groundwater , 2010 .
[18] Fabio Divino,et al. Disease mapping models: an empirical evaluation , 2000 .
[19] Mark Jenkinson,et al. Imaging dopamine receptors in humans with [11C]-(+)-PHNO: Dissection of D3 signal and anatomy , 2011, NeuroImage.
[20] Jouko Lampinen,et al. Bayesian Model Assessment and Comparison Using Cross-Validation Predictive Densities , 2002, Neural Computation.
[21] 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.
[22] Karl J. Friston,et al. Bayesian fMRI time series analysis with spatial priors , 2005, NeuroImage.
[23] Purushottam W. Laud,et al. Approximate Random Variate Generation from Infinitely Divisible Distributions with Applications to Bayesian Inference , 1995 .
[24] Joseph E LeDoux,et al. Contributions of the Amygdala to Emotion Processing: From Animal Models to Human Behavior , 2005, Neuron.
[25] Paul Gustafson,et al. On cross‐validation of Bayesian models , 2001 .
[26] T. Ferguson. A Bayesian Analysis of Some Nonparametric Problems , 1973 .
[27] Peter J. Diggle,et al. Statistical analysis of spatial point patterns , 1983 .
[28] Stephen M. Smith,et al. Functional MRI : an introduction to methods , 2002 .
[29] M. Escobar,et al. Bayesian Density Estimation and Inference Using Mixtures , 1995 .
[30] S.C. Strother,et al. Evaluating fMRI preprocessing pipelines , 2006, IEEE Engineering in Medicine and Biology Magazine.
[31] Sylvia Richardson,et al. Inference and monitoring convergence , 1995 .
[32] D. Ruppert. The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .
[33] T. Yarkoni. Big Correlations in Little Studies: Inflated fMRI Correlations Reflect Low Statistical Power—Commentary on Vul et al. (2009) , 2009, Perspectives on psychological science : a journal of the Association for Psychological Science.
[34] Harri HöUgmander,et al. Multitype Spatial Point Patterns with Hierarchical Interactions , 1999 .
[35] D. Stoyan,et al. Recent applications of point process methods in forestry statistics , 2000 .
[36] Ralph Adolphs,et al. The Human Amygdala and Emotion , 1999 .
[37] Michael I. Jordan,et al. A Sticky HDP-HMM With Application to Speaker Diarization , 2009, 0905.2592.
[38] A. Balakrishnan,et al. Spectral theory of random fields , 1983 .
[39] D. Rubin,et al. Inference from Iterative Simulation Using Multiple Sequences , 1992 .
[40] Lars Kai Hansen,et al. Modeling of activation data in the BrainMap™ database: Detection of outliers , 2002, Human brain mapping.
[41] Perry R. Cook,et al. Data-Driven Recomposition using the Hierarchical Dirichlet Process Hidden Markov Model , 2009, ICMC.
[42] D. Stoyan,et al. Statistical Analysis and Modelling of Spatial Point Patterns , 2008 .
[43] M. Lindquist,et al. Meta-analysis of functional neuroimaging data: current and future directions. , 2007, Social cognitive and affective neuroscience.
[44] M. Raichle. Functional Brain Imaging and Human Brain Function , 2003, The Journal of Neuroscience.
[45] Thomas E. Nichols,et al. Diagnosis and exploration of massively univariate neuroimaging models , 2003, NeuroImage.
[46] Tom M. Mitchell,et al. Machine learning classifiers and fMRI: A tutorial overview , 2009, NeuroImage.
[47] Adrian Baddeley,et al. Centrum Voor Wiskunde En Informatica Probability, Networks and Algorithms Probability, Networks and Algorithms Extrapolating and Interpolating Spatial Patterns Extrapolating and Interpolating Spatial Patterns , 2022 .
[48] Anders Brix,et al. Space‐time Multi Type Log Gaussian Cox Processes with a View to Modelling Weeds , 2001 .
[49] W. Gilks,et al. Adaptive Rejection Sampling for Gibbs Sampling , 1992 .
[50] Peter J. Diggle,et al. A Conditional Approach to Point Process Modelling of Elevated Risk , 1994 .
[51] Karl J. Friston,et al. Statistical parametric maps in functional imaging: A general linear approach , 1994 .
[52] Thomas E. Nichols,et al. Image-based vs. Coordinate-based Meta-analysis , 2009, NeuroImage.
[53] Sarat C. Dass,et al. Assessing Fingerprint Individuality Using EPIC: A Case Study in the Analysis of Spatially Dependent Marked Processes , 2011, Technometrics.
[54] C Gössl,et al. Bayesian Spatiotemporal Inference in Functional Magnetic Resonance Imaging , 2001, Biometrics.
[55] Jesper Møller,et al. Hierarchical spatial point process analysis for a plant community with high biodiversity , 2009, Environmental and Ecological Statistics.
[56] Guinevere F. Eden,et al. Meta-Analysis of the Functional Neuroanatomy of Single-Word Reading: Method and Validation , 2002, NeuroImage.
[57] A. P. Wills,et al. The Magnetic Susceptibility of Oxygen, Hydrogen and Helium , 1924 .
[58] Stephen José Hanson,et al. Decoding the Large-Scale Structure of Brain Function by Classifying Mental States Across Individuals , 2009, Psychological science.
[59] A. Gelfand,et al. The Nested Dirichlet Process , 2008 .
[60] Aki Niemi,et al. Bayesian Spatial Point Process Modeling of Line Transect Data , 2010 .
[61] J. Jonides,et al. Elements of Functional Neuroimaging 1 ELEMENTS OF FUNCTIONAL NEUROIMAGING , 2007 .
[62] Eric P. Xing,et al. Hidden Markov Dirichlet process: modeling genetic inference in open ancestral space , 2007 .
[63] F Dubois Bowman,et al. Spatio-temporal modeling of localized brain activity. , 2005, Biostatistics.
[64] Thomas L. Griffiths,et al. The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies , 2007, JACM.
[65] 耕太 片野田,et al. A spatio-temporal regression model for the analysis of functional MRI data , 2002 .
[66] R. Poldrack. Can cognitive processes be inferred from neuroimaging data? , 2006, Trends in Cognitive Sciences.
[67] R. Wolpert,et al. Poisson/gamma random field models for spatial statistics , 1998 .
[68] Peter J. Diggle,et al. Nonparametric estimation of spatial segregation in a multivariate point process: bovine tuberculosis in Cornwall, UK , 2005 .
[69] R. Wolpert,et al. Spatial Regression for Marked Point Processes , 2008 .
[70] Mark W. Woolrich,et al. Mixture models with adaptive spatial regularization for segmentation with an application to FMRI data , 2005, IEEE Transactions on Medical Imaging.
[71] N. G. Best,et al. Spatial Poisson Regression for Health and Exposure Data Measured at Disparate Resolutions , 2000 .
[72] C. Antoniak. Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems , 1974 .
[73] Martin A. Lindquist,et al. Evaluating the consistency and specificity of neuroimaging data using meta-analysis , 2009, NeuroImage.
[74] Marcus E. Raichle,et al. Functional Neuroimaging: A Historical and Physiological Perspective , 2001 .
[75] Sophie Achard. The Statistical Analysis of Functional MRI Data , 2008 .
[76] Peter J. Diggle,et al. Bivariate Cox Processes: Some Models for Bivariate Spatial Point Patterns , 1983 .
[77] L. Bondesson. On simulation from infinitely divisible distributions , 1982, Advances in Applied Probability.
[78] D. V. Essen,et al. Cognitive neuroscience 2.0: building a cumulative science of human brain function , 2010, Trends in Cognitive Sciences.
[79] M. Lindquist. The Statistical Analysis of fMRI Data. , 2008, 0906.3662.
[80] J. Møller,et al. Log Gaussian Cox Processes , 1998 .
[81] Hong Chang,et al. Model Determination Using Predictive Distributions with Implementation via Sampling-Based Methods , 1992 .
[82] Thomas E. Nichols,et al. Meta Analysis of Functional Neuroimaging Data via Bayesian Spatial Point Processes , 2011, Journal of the American Statistical Association.
[83] Michael I. Jordan,et al. Hierarchical Dirichlet Processes , 2006 .
[84] A. Baddeley,et al. Residual analysis for spatial point processes (with discussion) , 2005 .
[85] Jean-Baptiste Poline,et al. Analysis of a large fMRI cohort: Statistical and methodological issues for group analyses , 2007, NeuroImage.
[86] Lisa Feldman Barrett,et al. Functional grouping and cortical–subcortical interactions in emotion: A meta-analysis of neuroimaging studies , 2008, NeuroImage.
[87] S. MacEachern. Decision Theoretic Aspects of Dependent Nonparametric Processes , 2000 .
[88] M. Hutchings,et al. Standing crop and pattern in pure stands of Mercurialis perennis and Rubus fruticosus in mixed deciduous woodland , 1978 .
[89] Scott A. Sisson,et al. Statistical Inference and Simulation for Spatial Point Processes , 2005 .
[90] W. Bradley,et al. MRI: The Basics , 1997 .