Multichannel least-squares linear regression provides a fast, accurate, unbiased and robust estimation of Granger causality for neurophysiological data

Computers in Biology and Medicine

Volumn 41, Issue 12, 2011, Pages 1118-1131

  Frye, Richard E ^a   Wu, Meng Hung ^b  

^a UNIVERSITY OF ARKANSAS FOR MEDICAL SCIENCES   (United States)

^b South Texas College   (United States)

Author keywords

Autoregressive models; Connectivity; Granger causality; Magnetoencephalography

Indexed keywords

AUTO REGRESSIVE MODELS; AUTO-REGRESSIVE; AUTOCORRELATION FUNCTIONS; CONNECTIVITY; GRANGER CAUSALITY; LEAST SQUARE; MULTI-CHANNEL; RESIDUAL ERROR; ROBINSON; ROBUST ESTIMATION;

ALGORITHMS; MAGNETOENCEPHALOGRAPHY; REGRESSION ANALYSIS;

LEAST SQUARES APPROXIMATIONS;

ACCURACY; ALGORITHM; ARTICLE; EPIDEMIOLOGY; ERROR; LINEAR REGRESSION ANALYSIS; MAGNETOENCEPHALOGRAPHY; NEUROPHYSIOLOGY; PRIORITY JOURNAL; SIMULATION;

ALGORITHMS; COMPUTER SIMULATION; HUMANS; LEAST-SQUARES ANALYSIS; LINEAR MODELS; MAGNETOENCEPHALOGRAPHY; SIGNAL PROCESSING, COMPUTER-ASSISTED; YOUNG ADULT;

EID: 82955237297     PISSN: 00104825     EISSN: 18790534     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2011.04.012     Document Type: Article

References (32)

1. Ramnani N., Behrens T.E., Penny W., Matthews P.M. New approaches for exploring anatomical and functional connectivity in the human brain. Biol. Psychiatry 2004, 56:613.
2. Sherbondy A., Akers D., Mackenzie R., Dougherty R., Wandell B. Exploring connectivity of the brain's white matter with dynamic queries. IEEE Trans. Vis. Comput. Graph. 2005, 11:419.
3. Astolfi L., Cincotti F., Mattia D., de Vico Fallani F., Lai L., Baccala M., Salinari S., Ursino M., Zavaglia M., Babiloni F. Comparison of different multivariate methods for the estimation of cortical connectivity: simulations and applications to EEG data. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2005, 5:4484.
4. He B.J., Shulman G.L., Snyder A.Z., Corbetta M. The role of impaired neuronal communication in neurological disorders. Curr. Opin. Neurol. 2007, 20:655.
5. Takigawa M., Wang G., Kawasaki H., Fukuzako H. EEG analysis of epilepsy by directed coherence method. A data processing approach. Int. J. Psychophysiol. 1996, 21:65.
6. Wendling F., Bartolomei F., Bellanger J.J., Chauvel P. Interpretation of interdependencies in epileptic signals using a macroscopic physiological model of the EEG. Clin. Neurophysiol. 2001, 112:1201.
7. Thatcher R.W., Biver C.J., North D. Spatial-temporal current source correlations and cortical connectivity. Clin. EEG Neurosci. 2007, 38:35.
8. Hamalainen M.S. Magnetoencephalography: a tool for functional brain imaging. Brain Topogr. 1992, 5:95.
9. Lee L., Harrison L.M., Mechelli A. A report of the functional connectivity workshop, Dusseldorf 2002. NeuroImage 2003, 19:457.
10. Schnitzler A., Gross J. Functional connectivity analysis in magnetoencephalography. Magnetoencephalography 2005, Elsevier, Boston. H. Preissl (Ed.).
11. Leuthold A.C., Langheim F.J., Lewis S.M., Georgopoulos A.P. Time series analysis of magnetoencephalographic data during copying. Exp. Brain Res. 2005, 164:411.
12. Kiebel S.J., David O., Friston K.J. Dynamic causal modelling of evoked responses in EEG/MEG with lead field parameterization. NeuroImage 2006, 30:1273.
13. Granger C.W.J. Testing for causality: a personal viewpoint. J. Econ. Dyn. Control 1980, 2:329.
14. R.E. Frye, M. Wu, G. Zouridakis, Dynamic autoregressive neuromagnetic causality imaging (DANCI), in: Proceedings of the WSEAS International Conference on Computers, 2007, pp. 304.
15. R.E. Frye, M. Wu, G. Zouridakis, J. Liederman, Causal prefrontal-temporoparietal interactions are correlated with word-rhyming performance in reading disabilities, biomagnetism: interdisciplinary research and exploration, in: Proceedings of Biomag 2008, pp. 248.
16. Frye R.E., Wu M.-H., Liederman J., McGraw Fisher J. Greater pre-stimulus effective connectivity from the left inferior frontal area to other areas is associated with better phonological decoding in dyslexic readers. Front. Syst. Neurosci. 2010, 4:156.
17. Granger C.W.J. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 1969, 37:424.
18. Cui J., Xu L., Bressler S.L., Ding M., Liang H. BSMART: a Matlab/C toolbox for analysis of multichannel neural time series. Neural Networks 2008, 21:1094.
19. Ding M., Chen Y., Bressler S.L. Granger causality: basic theory and application to neuroscience. Handbook of Time Series Analysis 2006, Wiley-VCH, Berlin, pp. 451. B. Schelter, M. Winterhalder, J. Timmer (Eds.).
20. Ding M., Bressler S.L., Yang W., Liang H. Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modeling: data preprocessing, model validation, and variability assessment. Biol. Cybern 2000, 83:35.
21. DeHoon M.J.L., Van Der Hagen T.H.J.J., Schoonewelle H., Van Dam H. Why Yule-Walker should not be used for autoregressive modelling. Ann. Nucl. Energy 1996, 23:1219-1228.
22. Seth A.K. Causal connectivity of evolved neural networks during behavior. Network 2005, 16:35.
23. Seth A.K., Edelman G.M. Distinguishing causal interactions in neural populations. Neural Comput. 2007, 19:910.
24. Seth A.K. A MATLAB toolbox for Granger causal connectivity analysis. J. Neurosci. Methods 2010, 186:262-273.
25. Seber G.A.F., Wild C.J. Nonlinear Regression 2003, John Wiley and Sons, Hoboken.
26. Florin E., Gross J., Pfeifer J., Fink G.R., Timmermann L. The effect of filtering on Granger causality based multivariate causality measures. NeuroImage 2009, 50:577.
27. Dhamala M., Rangarajan G., Ding M. Analyzing information flow in brain networks with nonparametric Granger causality. NeuroImage 2008, 41:354.
28. Dhamala M., Rangarajan G., Ding M. Estimating Granger causality from fourier and wavelet transforms of time series data. Phys. Rev. Lett. 2008, 100:018701.
29. Box G., Jenkins G. Time Series Analysis: Forecasting and Control 1970, Holden Day, San Francisco.
30. Kaminski M., Liang H. Causal influence: advances in neurosignal analysis. Crit. Rev. Biomed. Eng. 2005, 33:347.
31. Chen Y., Rangarajan G., Feng J., Ding M. Analyzing multiple nonlinear time series with extended Granger causality. Phys. Rev. Lett. 2004, 324:26.
32. M. Wu, R. Frye, G. Zouridakis, A comparison of multivariate causality based measures of effective connectivity, Comp. Bio. Med., this issue.