[1]
|
Astolfi, L., Cincotti, F., Mattia, D., Salinari, S., Babiloni, C. and Basilisco, A., et al. (2004) Estimation of the effective and functional human cortical connectivity with structural equation modeling and directed transfer function applied to high-resolution EEG. Magn Reson Imaging, 22(10), 1457-1470.
|
[2]
|
Brovelli, A., Ding, M.Z., Ledberg, A., Chen, Y.H., Nakamura, R. and Bressler, S.L. (2004) Beta oscillations in a large- scale sensorimotor cortical network: Directional influences revealed by Granger causality. Proceedings of the National Academy of Sciences of the United States of America, 101(26), 9849-9854.
|
[3]
|
Eichler, M. (2005) A graphical approach for evaluating effective connectivity in neural systems. Philos Trans R Soc Lond B Biol Sci, 360(1457), 953-967.
|
[4]
|
Sato, J.R., Amaro, E.D. Takahashi, Y., Felix, M.D., Brammer, M.J. and Morettin, P.A. (2006) A method to produce evolving functional connectivity maps during the course of an fMRI experiment using wavelet-based time-varying Granger causality. Neuroimage, 31(1), 187- 196.
|
[5]
|
Smith, J.F., Pillai, A., Chen, K. and Horwitz, B. (2009) Identification and validation of effective connectivity ne- tworks in functional magnetic resonance imaging using switching linear dynamic systems. Neuroimage, 52(3), 1027-1040.
|
[6]
|
Chen, H.F., Yang, Q., Liao, W., Gong, Q. Y. and Shen, S. (2009) Evaluation of the effective connectivity of supple- mentary motor areas during motor imagery using Gra- nger causality mapping. Neuroimage, 47(4), 1844-1853.
|
[7]
|
Geweke, J. (1982) The measurement of Linear dependence and feedback between multiple Time-Series rejoinder. Journal of the American Statistical Association, 77 (378), 323-324.
|
[8]
|
Gow, Jr, D.W., Segawa, J.A., Ahlfors, S.P. and Lin, F.H. (2008) Lexical influences on speech perception: A Granger causality analysis of MEG and EEG source estimates. Neuroimage, 43(3), 614-623.
|
[9]
|
Liao, W., Mantini, D., Zhang, Z., Pan, Z., Ding J. and Gong, Q. et al. (2010) Evaluating the effective connectivity of resting state networks using conditional Granger causality. Biological. Cybernetics, 102(1), 57-69.
|
[10]
|
Liao, W., Marinazzo, D., Pan, Z., Gong, Q. and Chen, H. Kernel Granger causality mapping effective connectivity on FMRI data. IEEE Trans Med Imaging, 28(11), 1825- 1835.
|
[11]
|
Lin, F.H., Hara, K., Solo, V., Vangel, M., Belliveau, J.W. and Stufflebeam, S.M., et al. (2009) Dynamic Granger- Geweke Causality Modeling With Application to Interictal Spike Propagation. Human Brain Mapping, 30(6), 1877-1886.
|
[12]
|
Marinazzo, D., Liao, W., Chen, H. and Stramaglia, S. (2010) Nonlinear connectivity by Granger causality. Ne- uroimage.
|
[13]
|
Box, G.E.P., Jenkins, G.M. and Reinsel, G.C. (1994) Time series analysis: Forecasting and control, Prentice Hall, New Jersey.
|
[14]
|
Chatfield, C. (2001) Time-series forecasting. Chapman & Hall/CRC.
|
[15]
|
Londei, A., D’Ausilio, A., Basso, D. and Belardinelli, M. O. (2006) A new method for detecting causality in fMRI data of cognitive processing. Cogn Process, 7(1), 42-52.
|
[16]
|
Nedungadi, A.G., Rangarajan, G., Jain, N. and Ding, M. Z. (2009) Analyzing multiple spike trains with nonparametric granger causality. Journal of Computational Neu- roscience, 27(1), 55-64.
|
[17]
|
Roebroeck, A., Formisano, E. and Goebel, R. (2005) Ma- pping directed influence over the brain using Granger causality and fMRI. Neuroimage, 25(1), 230-242.
|
[18]
|
Zhang, Y., Chen, Y., Bressler, S.L. and Ding, M. (2008) Response preparation and inhibition: The role of the cortical sensorimotor beta rhythm. Neuroscience, 156(1), 238-246.
|
[19]
|
Kong, J., Gollub, R.L., Webb, J.M., Kong, J.T., Vangel, M.G. and Kwong, K. (2007) Test-retest study of fMRI signal change evoked by electroacupuncture stimulation. Neuroimage, 34(3), 1171-1181.
|
[20]
|
Greene, W.H., (2003) Econometric analysis. Prentice Ha- ll, New Jersey.
|
[21]
|
Yaffee, R.A. and McGee, M. (2000) Introduction to time series analysis and forecasting: With applications in SAS and SPSS. Academic Press,USA.
|
[22]
|
Dickey, D.A. and Fuller, W.A. (1979) Distribution of the Estimators for Autoregressive Time-Series with a Unit Root. Journal of the American Statistical Association, 74(366), 427-431.
|
[23]
|
Neumaier, A. and Schneider, T. (2001) Estimation of parameters and eigenmodes of multivariate autoregressive models. Acm Transactions on Mathematical Software, 27(1), 27-57.
|
[24]
|
Notle, J. (1999) The Human Brain: An Introduction to its functional anatomy. Mosby Inc., Louis.
|
[25]
|
Friston, K.J., Ashburner, J.T., Kiebel, S.J., Nichols, T.E. and Penny, W.D. (2007) Statistical parametric mapping. Elsevier. Academic Press, USA.
|
[26]
|
Priestley, M.B. (1981) Spectral analysis and time series. Academic Press, USA.
|
[27]
|
Priestley, M.B. (1988) Non-linear and non-stationary time series analysis. Academic, USA.
|
[28]
|
Wei, W. (2006) Time Series Analysis. Perrson Education, inc., Chichester.
|
[29]
|
Pearl, J. (2000) Causality: Models, reasoning, and inference. Cambridge University Press, UK.
|
[30]
|
Brooks, C. (2008) Introductory econometrics for finance. Cambridge University Press, UK.
|
[31]
|
Baum, C.F. (2006) An introduction to modern econometrics using Stata. Stata Press, Texas.
|
[32]
|
Warner, R.M. (1998) Spectral analysis of time-series data. Guilford Press, New York.
|
[33]
|
Mills, T.C. (1990) Time series techniques for economists, Cambridge University Press, UK.
|
[34]
|
Clements, P. and Hendry, D.F. (1999) Forecasting non- stationary economic time series. MIT Press, Cambridge.
|
[35]
|
Storch, H.V. and Zwiers, F.W. (1999) Statistical analysis in climate research. Cambridge University Press, UK.
|
[36]
|
Kirchg?ssner, G. and Wolters, J. (2007) Introduction to modern time series analysis. Springer, New York.
|
[37]
|
Hochberg, Y. (1988) A Sharper Bonferroni Procedure for Multiple Tests of Significance. Biometrika, 75(4), 800- 802.
|