contribution with the linear multivariate time series models

[1]  Deborah A. Hall,et al.  Connectivity analysis with structural equation modelling: an example of the effects of voxel selection , 2003, NeuroImage.

[2]  Silke Dodel,et al.  Functional connectivity: studying nonlinear, delayed interactions between BOLD signals , 2003, NeuroImage.

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

[4]  Luiz A. Baccalá,et al.  Partial directed coherence: a new concept in neural structure determination , 2001, Biological Cybernetics.

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

[6]  P. König,et al.  Bi‐directional interactions between visual areas in the awake behaving cat , 2000, Neuroreport.

[7]  Clifford M. Hurvich,et al.  Regression and time series model selection in small samples , 1989 .

[8]  James D. Hamilton.  Time Series Analysis , 1994 .

[9]  H. Akaike.  On the use of a linear model for the identification of feedback systems , 1968 .

[10]  Alan C. Evans,et al.  A General Statistical Analysis for fMRI Data , 2000, NeuroImage.

[11]  Andrea Mechelli,et al.  The Functional Brain Connectivity Workshop: report and commentary , 2003, Network.

[12]  Venkataramanan Balakrishnan,et al.  System identification: theory for the user (second edition): Lennart Ljung; Prentice-Hall, Englewood Cliffs, NJ, 1999, ISBN 0-13-656695-2 , 2002, Autom..

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

[14]  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.

[15]  J. Geweke,et al.  Measures of Conditional Linear Dependence and Feedback between Time Series , 1984 .

[16]  Yuzo Hosoya.  The decomposition and measurement of the interdependency between second-order stationary processes , 1991 .

[17]  C. Granger.  Investigating Causal Relations by Econometric Models and Cross-Spectral Methods , 1969 .

[18]  G. Jackson,et al.  Changes in effective connectivity models in the presence of task‐correlated motion: An fMRI study , 2004, Human brain mapping.

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

[20]  Yuzo Hosoya.  Elimination of Third‐series Effect and Defining Partial Measures of Causality , 2001 .

[21]  David S. Stoffer,et al.  Time series analysis and its applications , 2000 .

[22]  E. Carlstein.  Resampling techniques for stationary time-series: Some recent developments , 1990 .

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

[24]  Peter König,et al.  On the directionality of cortical interactions studied by structural analysis of electrophysiological recordings , 1999, Biological Cybernetics.

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

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

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

[28]  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.

[29]  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.

[30]  J. Geweke,et al.  Measurement of Linear Dependence and Feedback between Multiple Time Series , 1982 .

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