Some Novel Spatial Stochastic Models for Functional Neuroimaging Analysis.

[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 .