Comparing dynamic causal models

[1]  Tony O’Hagan Bayes factors , 2006 .

[2]  David J. C. MacKay,et al.  Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.

[3]  Konrad P. Körding,et al.  Integrating Top-Down and Bottom-Up Sensory Processing by Somato-Dendritic Interactions , 2004, Journal of Computational Neuroscience.

[4]  Karl J. Friston,et al.  A Dynamic Causal Modeling Study on Category Effects: BottomUp or TopDown Mediation? , 2003, Journal of Cognitive Neuroscience.

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

[6]  A. Caspi,et al.  Influence of Life Stress on Depression: Moderation by a Polymorphism in the 5-HTT Gene , 2003, Science.

[7]  Karl J. Friston,et al.  Lateralized Cognitive Processes and Lateralized Task Control in the Human Brain , 2003, Science.

[8]  J. B. Levitt,et al.  Circuits for Local and Global Signal Integration in Primary Visual Cortex , 2002, The Journal of Neuroscience.

[9]  Klaas E. Stephan,et al.  The anatomical basis of functional localization in the cortex , 2002, Nature Reviews Neuroscience.

[10]  Karl J. Friston,et al.  Bayesian Estimation of Dynamical Systems: An Application to fMRI , 2002, NeuroImage.

[11]  William H. Press,et al.  Numerical recipes in C , 2002 .

[12]  M. Young,et al.  Advanced database methodology for the Collation of Connectivity data on the Macaque brain (CoCoMac). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[13]  Refractor Vision , 2000, The Lancet.

[14]  José M Bernardo and Adrian F M Smith Bayesian Theory , 2001 .

[15]  Leslie G. Ungerleider,et al.  The Representation of Objects in the Human Occipital and Temporal Cortex , 2000, Journal of Cognitive Neuroscience.

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

[17]  Karl J. Friston,et al.  Attentional modulation of effective connectivity from V2 to V5/MT in humans. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[18]  E. Bullmore,et al.  How Good Is Good Enough in Path Analysis of fMRI Data? , 2000, NeuroImage.

[19]  Adrian E. Raftery,et al.  Bayesian model averaging: a tutorial (with comments by M. Clyde, David Draper and E. I. George, and a rejoinder by the authors , 1999 .

[20]  Karl J. Friston,et al.  The physiological basis of attentional modulation in extrastriate visual areas , 1999, Nature Neuroscience.

[21]  Leslie G. Ungerleider,et al.  Increased Activity in Human Visual Cortex during Directed Attention in the Absence of Visual Stimulation , 1999, Neuron.

[22]  R. Desimone,et al.  Competitive Mechanisms Subserve Attention in Macaque Areas V2 and V4 , 1999, The Journal of Neuroscience.

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

[24]  R. Buxton,et al.  Dynamics of blood flow and oxygenation changes during brain activation: The balloon model , 1998, Magnetic resonance in medicine.

[25]  M. Hallett Human Brain Function , 1998, Trends in Neurosciences.

[26]  Leslie G. Ungerleider,et al.  A neural system for human visual working memory. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[27]  Jorma Rissanen,et al.  Stochastic Complexity in Statistical Inquiry , 1989, World Scientific Series in Computer Science.

[28]  F. Aboitiz,et al.  The evolutionary origin of the language areas in the human brain. A neuroanatomical perspective , 1997, Brain Research Reviews.

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

[30]  A. Burkhalter,et al.  A Polysynaptic Feedback Circuit in Rat Visual Cortex , 1997, The Journal of Neuroscience.

[31]  L. Wasserman,et al.  Computing Bayes Factors by Combining Simulation and Asymptotic Approximations , 1997 .

[32]  A. Treisman,et al.  Voluntary Attention Modulates fMRI Activity in Human MT–MST , 1997, Neuron.

[33]  R. Desimone,et al.  Neural mechanisms of spatial selective attention in areas V1, V2, and V4 of macaque visual cortex. , 1997, Journal of neurophysiology.

[34]  John H. R. Maunsell,et al.  Attentional modulation of visual motion processing in cortical areas MT and MST , 1996, Nature.

[35]  T D Albright,et al.  Visual motion perception. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[36]  A. Raftery Bayesian Model Selection in Social Research , 1995 .

[37]  Yoshua Bengio,et al.  Pattern Recognition and Neural Networks , 1995 .

[38]  Adrian E. Raftery,et al.  Bayes factors and model uncertainty , 1995 .

[39]  Leslie G. Ungerleider,et al.  Network analysis of cortical visual pathways mapped with PET , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[40]  Karl J. Friston,et al.  Statistical parametric maps in functional imaging: A general linear approach , 1994 .

[41]  Karl J. Friston,et al.  A direct demonstration of functional specialization in human visual cortex , 1991, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[42]  P. Goldman-Rakic,et al.  Preface: Cerebral Cortex Has Come of Age , 1991 .

[43]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[44]  D. J. Felleman,et al.  Distributed hierarchical processing in the primate cerebral cortex. , 1991, Cerebral cortex.

[45]  H. Bozdogan Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions , 1987 .

[46]  John G. Proakis,et al.  Probability, random variables and stochastic processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[47]  Bruno O. Shubert,et al.  Random variables and stochastic processes , 1979 .

[48]  G. Schwarz Estimating the Dimension of a Model , 1978 .

[49]  H. Akaike,et al.  Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .

[50]  C. S. Wallace,et al.  An Information Measure for Classification , 1968, Comput. J..

[51]  L. Goddard Information Theory , 1962, Nature.

[52]  H. Jeffreys Some Tests of Significance, Treated by the Theory of Probability , 1935, Mathematical Proceedings of the Cambridge Philosophical Society.