Full-brain auto-regressive modeling (FARM) using fMRI

[1]  P. Brockwell,et al.  Time Series: Theory and Methods , 2013 .

[2]  Michael T. Lippert,et al.  Coupling of neural activity and fMRI-BOLD in the motion area MT. , 2010, Magnetic resonance imaging.

[3]  Benjamin Thyreau,et al.  Discriminative Network Models of Schizophrenia , 2009, NIPS.

[4]  Justin L. Vincent,et al.  Precuneus shares intrinsic functional architecture in humans and monkeys , 2009, Proceedings of the National Academy of Sciences.

[5]  Karl J. Friston,et al.  Causal Hierarchy within the Thalamo-Cortical Network in Spike and Wave Discharges , 2009, PloS one.

[6]  Rahul Garg,et al.  Gradient descent with sparsification: an iterative algorithm for sparse recovery with restricted isometry property , 2009, ICML '09.

[7]  Xiaoping Hu,et al.  Multivariate Granger causality analysis of fMRI data , 2009, Human brain mapping.

[8]  Kaiming Li,et al.  Review of methods for functional brain connectivity detection using fMRI , 2009, Comput. Medical Imaging Graph..

[9]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.

[10]  A. Ravishankar Rao,et al.  Prediction and interpretation of distributed neural activity with sparse models , 2009, NeuroImage.

[11]  Ravi Iyengar,et al.  Ordered cyclic motifs contribute to dynamic stability in biological and engineered networks , 2008, Proceedings of the National Academy of Sciences.

[12]  Martin A. Lindquist,et al.  Detection of time-varying signals in event-related fMRI designs , 2008, NeuroImage.

[13]  Peter Fransson,et al.  The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: Evidence from a partial correlation network analysis , 2008, NeuroImage.

[14]  N. Logothetis.  What we can do and what we cannot do with fMRI , 2008, Nature.

[15]  Tom Michael Mitchell,et al.  Predicting Human Brain Activity Associated with the Meanings of Nouns , 2008, Science.

[16]  A. Ravishankar Rao,et al.  Inferring brain dynamics using granger causality on fMRI data , 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[17]  João Ricardo Sato,et al.  Wavelet based time-varying vector autoregressive modelling , 2007, Comput. Stat. Data Anal..

[18]  Dante R Chialvo,et al.  Identifying directed links in large scale functional networks: application to brain fMRI , 2007, BMC Cell Biology.

[19]  Jeremy I. Skipper,et al.  Speech-associated gestures, Broca’s area, and the human mirror system , 2007, Brain and Language.

[20]  Edward T. Bullmore,et al.  Frequency based mutual information measures between clusters of brain regions in functional magnetic resonance imaging , 2007, NeuroImage.

[21]  Danielle Smith Bassett,et al.  Small-World Brain Networks , 2006, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[22]  Sean M. Polyn,et al.  Beyond mind-reading: multi-voxel pattern analysis of fMRI data , 2006, Trends in Cognitive Sciences.

[23]  Yingli Lu,et al.  Using voxel-specific hemodynamic response function in EEG-fMRI data analysis , 2006, NeuroImage.

[24]  Habib Benali,et al.  Partial correlation for functional brain interactivity investigation in functional MRI , 2006, NeuroImage.

[25]  A. Cavanna,et al.  The precuneus: a review of its functional anatomy and behavioural correlates. , 2006, Brain : a journal of neurology.

[26]  C. Stam,et al.  Small-world networks and functional connectivity in Alzheimer's disease. , 2006, Cerebral cortex.

[27]  E. Bullmore,et al.  A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs , 2006, The Journal of Neuroscience.

[28]  Michael J. Berry,et al.  Weak pairwise correlations imply strongly correlated network states in a neural population , 2005, Nature.

[29]  Rodrigo Quian Quiroga,et al.  Nonlinear multivariate analysis of neurophysiological signals , 2005, Progress in Neurobiology.

[30]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[31]  E. Bullmore,et al.  Undirected graphs of frequency-dependent functional connectivity in whole brain networks , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[32]  Michael Eichler,et al.  A graphical approach for evaluating effective connectivity in neural systems , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[33]  Lester Melie-García,et al.  Estimating brain functional connectivity with sparse multivariate autoregression , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[34]  Gary H. Glover,et al.  Breath holding reveals differences in fMRI BOLD signal in children and adults , 2005, NeuroImage.

[35]  M. Small.  Applied Nonlinear Time Series Analysis: Applications in Physics, Physiology and Finance , 2005 .

[36]  A. Seth.  Causal connectivity of evolved neural networks during behavior. , 2005, Network.

[37]  Rainer Goebel,et al.  Mapping directed influence over the brain using Granger causality and fMRI , 2005, NeuroImage.

[38]  R. Buxton,et al.  Modeling the hemodynamic response to brain activation , 2004, NeuroImage.

[39]  Karl J. Friston,et al.  Comparing dynamic causal models , 2004, NeuroImage.

[40]  S. Bressler,et al.  Beta oscillations in a large-scale sensorimotor cortical network: directional influences revealed by Granger causality. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[41]  Mark D'Esposito,et al.  Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses , 2004, NeuroImage.

[42]  M. Greicius,et al.  Default-mode network activity distinguishes Alzheimer's disease from healthy aging: Evidence from functional MRI , 2004, Proc. Natl. Acad. Sci. USA.

[43]  Lee M. Miller,et al.  Measuring interregional functional connectivity using coherence and partial coherence analyses of fMRI data , 2004, NeuroImage.

[44]  Rainer Goebel,et al.  Investigating directed cortical interactions in time-resolved fMRI data using vector autoregressive modeling and Granger causality mapping. , 2003, Magnetic resonance imaging.

[45]  M. D’Esposito,et al.  Alterations in the BOLD fMRI signal with ageing and disease: a challenge for neuroimaging , 2003, Nature Reviews Neuroscience.

[46]  Jiahui Wang,et al.  Modeling Financial Time Series with S-PLUS® , 2003 .

[47]  G. Cecchi,et al.  Scale-free brain functional networks. , 2003, Physical review letters.

[48]  Karl J. Friston,et al.  Dynamic causal modelling , 2003, NeuroImage.

[49]  Peter Green,et al.  Highly Structured Stochastic Systems , 2003 .

[50]  Gabriele Lohmann,et al.  Within-subject variability of BOLD response dynamics , 2003, NeuroImage.

[51]  Karl J. Friston,et al.  Modeling regional and psychophysiologic interactions in fMRI: the importance of hemodynamic deconvolution , 2003, NeuroImage.

[52]  W. Grodd,et al.  Parametric analysis of rate-dependent hemodynamic response functions of cortical and subcortical brain structures during auditorily cued finger tapping: a fMRI study , 2003, NeuroImage.

[53]  Vinod Menon,et al.  Functional connectivity in the resting brain: A network analysis of the default mode hypothesis , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[54]  Silke Dodel,et al.  Functional connectivity by cross-correlation clustering , 2002, Neurocomputing.

[55]  T. Sejnowski,et al.  Single-Trial Variability in Event-Related BOLD Signals , 2002, NeuroImage.

[56]  L. Deecke,et al.  The Preparation and Execution of Self-Initiated and Externally-Triggered Movement: A Study of Event-Related fMRI , 2002, NeuroImage.

[57]  Mingzhou Ding,et al.  Evaluating causal relations in neural systems: Granger causality, directed transfer function and statistical assessment of significance , 2001, Biological Cybernetics.

[58]  C. Gilbert,et al.  Learning to see: experience and attention in primary visual cortex , 2001, Nature Neuroscience.

[59]  G. Shulman,et al.  Medial prefrontal cortex and self-referential mental activity: Relation to a default mode of brain function , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[60]  K. Amunts,et al.  Broca's region subserves imagery of motion: A combined cytoarchitectonic and fMRI study , 2000, Human brain mapping.

[61]  Karl J. Friston,et al.  Nonlinear Responses in fMRI: The Balloon Model, Volterra Kernels, and Other Hemodynamics , 2000, NeuroImage.

[62]  L. Jäncke,et al.  Cortical activations during paced finger-tapping applying visual and auditory pacing stimuli. , 2000, Brain research. Cognitive brain research.

[63]  Ravi S. Menon,et al.  Spatial and temporal limits in cognitive neuroimaging with fMRI , 1999, Trends in Cognitive Sciences.

[64]  G. Glover.  Deconvolution of Impulse Response in Event-Related BOLD fMRI1 , 1999, NeuroImage.

[65]  Michael A. Saunders,et al.  Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..

[66]  M. D’Esposito,et al.  The Variability of Human, BOLD Hemodynamic Responses , 1998, NeuroImage.

[67]  J. Pearl.  Graphs, Causality, and Structural Equation Models , 1998 .

[68]  Ravi S. Menon,et al.  Mental chronometry using latency-resolved functional MRI. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[69]  C.W. Anderson,et al.  Multivariate autoregressive models for classification of spontaneous electroencephalographic signals during mental tasks , 1998, IEEE Transactions on Biomedical Engineering.

[70]  D. Noll,et al.  Nonlinear Aspects of the BOLD Response in Functional MRI , 1998, NeuroImage.

[71]  C. Büchel,et al.  Modulation of connectivity in visual pathways by attention: cortical interactions evaluated with structural equation modelling and fMRI. , 1997, Cerebral cortex.

[72]  A. Grinvald,et al.  Dynamics of Ongoing Activity: Explanation of the Large Variability in Evoked Cortical Responses , 1996, Science.

[73]  Balas K. Natarajan,et al.  Sparse Approximate Solutions to Linear Systems , 1995, SIAM J. Comput..

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

[75]  C. Granger.  Investigating causal relations by econometric models and cross-spectral methods , 1969 .

[76]  J. P. Hamilton,et al.  Granger Causality via Vector Auto-Regression Tuned for FMRI Data Analysis , 2009 .

[77]  Richard M. Leahy,et al.  Functional Imaging of Brain Activity and Connectivity with MEG , 2007 .

[78]  Peter Machamer,et al.  Thinking about causes : from Greek philosophy to modern physics , 2007 .

[79]  Karl J. Friston,et al.  Statistical parametric mapping , 2013 .

[80]  Viktor K. Jirsa,et al.  Handbook of Brain Connectivity , 2007 .

[81]  D. Shasha,et al.  Sparse solutions for linear prediction problems , 2006 .

[82]  Justin Romberg,et al.  Practical Signal Recovery from Random Projections , 2005 .

[83]  H. Kinoshita,et al.  The effect of tapping finger and mode differences on cortical and subcortical activities: a PET study , 2004, Experimental Brain Research.

[84]  Karl J. Friston,et al.  Multivariate Autoregressive Modelling of fMRI time series , 2003 .

[85]  G. Edelman,et al.  A Universe Of Consciousness: How Matter Becomes Imagination , 2000 .

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

[87]  R. Tibshirani.  Regression Shrinkage and Selection via the Lasso , 1996 .

[88]  R. Passingham,et al.  Functional anatomy of the mental representation of upper extremity movements in healthy subjects. , 1995, Journal of neurophysiology.

[89]  Karl J. Friston.  Functional and effective connectivity in neuroimaging: A synthesis , 1994 .

[90]  F. Gonzalez-Lima,et al.  Structural equation modeling and its application to network analysis in functional brain imaging , 1994 .

[91]  E. Candès.  The restricted isometry property and its implications for compressed sensing , 2008 .

[92]  R. Tibshirani,et al.  Least angle regression , 2004, math/0406456.