Estimation of cortical connectivity from EEG using state-space models

IEEE Transactions on Biomedical Engineering

Volumn 57, Issue 9, 2010, Pages 2122-2134

  Cheung, Bing Leung Patrick ^a   Riedner, Brady Alexander ^b   Tononi, Giulio ^b   Van Veen, Barry D ^a  

^a University of Wisconsin Madison   (United States)

^b UNIVERSITY OF WISCONSIN SCHOOL OF MEDICINE AND PUBLIC HEALTH   (United States)

Author keywords

Effective connectivity; expectation maximization (EM) algorithm; Granger causality; multivariate autoregressive (MVAR) models; state space models

Indexed keywords

EFFECTIVE CONNECTIVITY; EXPECTATION-MAXIMIZATION (EM) ALGORITHM; GRANGER CAUSALITY; MULTIVARIATE AUTOREGRESSIVE; STATE-SPACE MODELS;

COMPUTER SIMULATION; COVARIANCE MATRIX; EQUATIONS OF STATE; ESTIMATION; MAXIMUM PRINCIPLE; OPTIMIZATION; SIZE DISTRIBUTION; STATE SPACE METHODS;

ALGORITHMS;

ARTICLE; BRAIN CORTEX; BRAIN REGION; ELECTROENCEPHALOGRAM; NOISE; SIMULATION;

ALGORITHMS; CEREBRAL CORTEX; COMPUTER SIMULATION; ELECTROENCEPHALOGRAPHY; HUMANS; MODELS, NEUROLOGICAL; MULTIVARIATE ANALYSIS; REGRESSION ANALYSIS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 77955870182     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2010.2050319     Document Type: Article

References (38)

1. H. Lutkepohl, Introduction to Multiple Time Series Analysis, 2nd ed. Berlin, Germany: Springer-Verlag, 1993.
2. S. Bressler, C. Richter, Y. Chen, and M. Ding, "Cortical functional network organization from autoregressive maodeling of local field potential oscillations," Statist. Med., vol.26, pp. 3875-3885, 2007.
3. M. Ding, Y. Chen, and L. Bressler, "Granger causality: Basic theory and application to neuroscience," Handbook of Time Series Analysis, B. Schelter, M. Winterhalder, and J. Timmer, Eds. Weinheim, Germany: Wiley, 2006, ch. 17, pp. 437-459.
4. C. Bernasconi and P. Konig, "On the directionality of cortical interactions studied by structural analysis of electrophysiological recordings," Biol. Cybern., vol.81, no.3, pp. 199-210, Sep. 1999.
5. A. Brovelli, M. Ding, A. Ledberg, Y. Chen, R. Nakamura, and S. Bressler, "Beta oscillations in a large-scale sensorimotor cortical network: Directional influences revealed by granger causality," Proc. Natl. Acad. Sci. USA, vol.101, no.26, pp. 9849-9854, Jun. 2004.
6. M.Winterhalder, B. Schelter,W. Hesse, K. Schwab, L. Leistritz, D. Klan, R. Bauer, J. Timmer, and H. Witte, "Comparison of linear signal processing techniques to infer directed interactions in multivariate neural system," Signal Process., vol.85, pp. 2137-2160, Nov. 2005.
7. J. Geweke, "Measurement of linear dependence and feedback between multiple time series," J. Amer. Statist. Assoc., vol.77, no.378, pp. 304- 313, Jun. 1982.
8. J. Geweke, "Measures of conditional linear dependence and feedback between time series," J. Amer. Statist. Assoc., vol.79, no.388, pp. 907- 915, Dec. 1984.
9. M. Kaminski, M. Ding, W. Truccolo, and S. Bressler, "Evaluating causal relations in neural systems: Granger causality, directed transfer function and statistical assessment of significance," Biol. Cybern., vol.85, no.2, pp. 145-157, Aug. 2001.
10. L. Baccala and K. Sameshima, "Partial directed coherence: A new concept in neural structure determination," Biol. Cybern., vol.84, no.6, pp. 463- 474, May 2001.
11. L. Ding, G. Worrell, T. Lagerlund, and B. He, "Ictal source analysis: Localization and imaging of causal interactions in humans," NeuroImage, vol.34, pp. 575-586, Jan. 2007.
12. F. Babiloni, F. Cinoctti, C. Babiloni, F. Carducci, D. Mattia, L. Astolfi, A. Basilisco, P. Rossini, L. Ding, Y. Ni, J. Cheng, K. Christine, J. Sweeney, and B. He, "Estimation of the cortical functional connectivity with the multimodal integration of high resolution EEG and fMRI data by directed transfer function," NeuroImage, vol.24, pp. 118-131, Jan. 2005.
13. L. Astolfi, F. Cincotti, D. Mattia, M. Marciani, L. Baccala, F. Fallani, S. Salinari, M. Ursino, M. Zavaglia, L. Ding, J. Edgar, G. Miller, B. He, and F. Babiloni, "Comparison of different cortical connectivity estimators for high-resolution EEG recordings," Human Brain Mapping, vol.28, pp. 143-157, Feb. 2007.
14. L. Astolfi, F. Cincotti, D. Mattia, F. Fallani, A. Tocci, A. Colosimo, A. Salinari, S. Salinari, M. Marciani, W. Hesse, H. White, M. Ursino, M. Zavaglia, and F. Babiloni, "Tracking the time-varying cortical connectivity patterns by adaptive multivariate estimators," IEEE Trans. Biomed. Eng., vol.55, no.3, pp. 902-913, Mar. 2008.
15. H. Hui, D. Pantazis, S. Bressler, and R. Leahy, "Identifying true cortical interactions inMEGusing the nulling beamformer," NeuroImage, vol.49, pp. 3161-3174, Feb. 2010.
16. S. Kay, Fundamentals of Statistical Signal Processing: Estimation Theory. Upper Saddle River, NJ: Prentice-Hall PTR, 1993.
17. L. Clement and O. Thas, "Estimating and modeling spatio-temporal correlation structures for river monitoring networks," J. Agric., Biol., Environ. Statist., vol.12, no.2, pp. 161-176, 2007.
18. K. Xu and C. Wikle, "Estimation of parameterized spatio-temporal dynamic models," J. Statist. Plann. Inference, vol.137, pp. 567-588, Feb. 2007.
19. R. Yamaguchi, R. Yoshida, S. Imoto, T. Higuchi, and S. Miyano, "Finding module-based gene networks with state-space models," IEEE Signal Process. Mag., vol.24, no.1, pp. 37-48, Jan. 2007.
20. H. Nalatore, M. Ding, and G. Rangarajan, "Denoising neural data with state-space smoothing: Method and application," J. Neurosci. Methods, vol.179, pp. 131-141, Apr. 2009.
21. R. Shumway and D. Stoffer, "An approach to time series smoothing and forecasting using the EM algorithm," J. Time Series Anal., vol.3, no.4, pp. 253-264, 1982.
22. B. Cheung, B. Riedner, G. Tononi, and B. Van Veen, "State-space multivariate autoregressive models for estimation of cortical connectivity from EEG," in Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. (EMBC), Minneapolis, MN, Sep. 2009, pp. 61-64.
23. B. Van Veen,W. van Drongelen,M. Yuchtman, and A. Suzuki, "Localization of brain electrical activity via linearly constrained minimum variance spatial filtering," IEEE Trans. Biomed. Eng., vol.44, no.9, pp. 867-880, Sep. 1997.
24. S. Baillet, J. Mosher, and R. Leahy, "Electromagnetic brain mapping," IEEE Signal Process. Mag., vol.18, no.6, pp. 14-30, Nov. 2001.
25. T. Limpiti, B. Van Veen, and R. Wakai, "Cortical patch basis model for spatially extended neural activity," IEEE Trans. Biomed. Eng., vol.53, no.9, pp. 1740-1754, Sep. 2006.
26. A. Dempster, N. Laird, and D. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. Roy. Statist. Soc., B, vol.39, no.1, pp. 1-38, 1977.
27. R. Kalman, "A new approach to linear filtering and prediction problems," Trans. ASME, J. Basic Eng., ser D, vol.82, pp. 35-45, Mar. 1960.
28. N. Gupta and R. Mehra, "Computational aspects of maximum likelihood estimation and reduction in sensitivity function calculations," IEEE Trans. Automat. Control, vol.AC-19, no.6, pp. 774-783, Dec. 1974.
29. C. Granger, "Investigating causal relations by econometric models and cross-spectral methods," Econometrica, vol.37, pp. 424-438, 1969.
30. Y. Chen, S. Bressler, and M. Ding, "Frequency decomposition of conditional granger causality and application to multivariate neural field potential data," J. Neurosci. Methods, vol.150, pp. 228-237, Jan. 2006.
31. G. Ganis, W. Thompson, and S. Kosslyn, "Brain areas underlying visual mental imagery and visual perception: An fmri study," Cogn. Brain Res., vol.20, pp. 226-241, Jul. 2004.
32. A. Mechelli, C. Price, K. Friston, and A. Ishai, "Where bottom-up meets top-down: Neuronal interactions during perception and imagery," Cereb. Cortex, vol.14, pp. 1256-1265, Jun. 2004.
33. H. Akaike, "A bayesian analysis of the minimum AIC procedure," Ann. Inst. Statist. Math., vol.30, no.1, pp. 9-14, Dec. 1978.
34. I. Miller and J. Freund, Probability and Statistics for Engineers, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall, 1977.
35. A. Bolstad, B. Van Veen, and R. Nowak, "Space-time event sparse penalization for magneto-/electroencephalography," NeuroImage, vol.46, pp. 1066-1081, Jul. 2009.
36. H. Rauch, F. Tung, and C. Stiebel, "Maximum likelihood estimates of linear dynamic systems," AIAA J., vol.3, pp. 1445-1450, 1965.
37. A. Pezeshki, B. Van Veen, L. Scharf, H. Cox, andM. Nordenvaad, "Eigenvalue beamforming using a multi-rank MVDR beamformer and subspace selection," IEEE Trans. Signal Process., vol.56, no.5, pp. 1954-1967, May 2008.
38. [Online]. Available: http://www.ece.wisc.edu/?vanveen/Pubs