Joint EEG/fMRI state space model for the detection of directed interactions in human brains - A simulation study

Physiological Measurement

Volumn 32, Issue 11, 2011, Pages 1725-1736

  Lenz, Michael ^a,b,c   Musso, Mariachristina ^b   Linke, Yannick ^a,b   Tüscher, Oliver ^b   Timmer, Jens ^a   Weiller, Cornelius ^b   Schelter, Björn ^a  

^a UNIVERSITY OF FREIBURG   (Germany)

^b UNIVERSITY OF FREIBURG   (Germany)

^c RWTH AACHEN UNIVERSITY   (Germany)

Author keywords

EEG fMRI fusion; effective connectivity; Kalman filter

Indexed keywords

BANDPASS FILTERS; BRAIN; BRAIN MAPPING; ELECTROENCEPHALOGRAPHY; ELECTROPHYSIOLOGY; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; MAGNETOENCEPHALOGRAPHY; MAXIMUM PRINCIPLE; NEURONS; PARAMETER ESTIMATION; STATE SPACE METHODS;

BRAIN NETWORKS; BRAIN REGIONS; CAUSAL RELATIONS; DIRECTED INTERACTIONS; EFFECTIVE CONNECTIVITIES; ELECTROENCEPHALOGRAPHY-FUNCTIONAL MAGNETIC RESONANCE IMAGING FUSION; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN BRAIN; SIMULATION STUDIES; STATE-SPACE MODELS;

KALMAN FILTERS;

EID: 80055031982     PISSN: 09673334     EISSN: 13616579     Source Type: Journal    
DOI: 10.1088/0967-3334/32/11/S01     Document Type: Article

References (19)

1. Baccala L A, Takahashi D Y and Sameshima K 2006 Handbook of Time Series Analysis ed B Schelter, M Winterhalder and J Timmer (New York: Wiley-VCH) pp 411-36
2. Cheung B L P, Riedner B, Tononi G and Van Veen B D 2009 State-space multivariate autoregressive models for estimation of cortical connectivity from EEG 31st Annu. Int. Conf. IEEE EMBS (Minneapolis, MN, USA, 2-6 Sept) pp 61-4
3. Cheung B L P and Van Veen B D 2008 Estimation of cortical multivariate autoregressive models for EEG/MEG using an expectation-maximization algorithm 5th IEEE Int. Symp. on Biomedical Imaging: Macro to Nano pp 1235-8
4. Deneux T and Faugeras O 2010 EEG-fMRI fusion of paradigm-free activity using Kalman filtering Neural Comput. 22 906-48
5. Eichler M 2005 A graphical approach for evaluating effective connectivity in neural systems Phil. Trans. Biol. Sci. 360 953-67 (Pubitemid 41672857)
6. Eichler M 2006 Handbook of Time Series Analysis ed B Schelter, M Winterhalder and J Timmer (New York: Wiley-VCH) pp 335-72
7. Friston K J, Harrison L and Penny W 2003 Dynamic causal modelling NeuroImage 19 1273-302 (Pubitemid 37025831)
8. Galka A, Wong K F K, Ozaki T, Muhle H, Stephani U and Siniatchkin M 2010 Decomposition of neurological multivariate time series by state space modelling Bull. Math. Biol. 73 285-324
9. Julier S J and Uhlmann J K 1997 A new extension of the Kalman filter to nonlinear systems Int. Symp. Aerospace/Defense Sensing, Simulation and Controls vol 3068 pp 182-93
10. Kandepu R, Foss B and Imsland L 2008 Applying the unscented Kalman filter for nonlinear state estimation J. Process Control 18 753-68
11. Kolas S, Foss B A and Schei T S 2009 Constrained nonlinear state estimation based on the UKF approach Comput. Chem. Eng. 33 1386-401
12. Limpiti T, Van Veen B D and Wakai R T 2006 Cortical patch basis model for spatially extended neural activity IEEE Trans. Biomed. Eng. 53 1740-54 (Pubitemid 44285902)
13. Mader W, Feess D, Lange R, Saur D, Glauche V, Weiller C, Timmer J and Schelter B 2008 On the detection of direct directed information flow in fMRI IEEE J. Sel. Top. Signal Process. 2 965-74
14. Nunez P L and Srinivasan R 2006 Electric Fields of the Brain: The Neurophysics of EEG (Oxford: Oxford University Press)
15. Sarkka S 2008 Unscented Rauch-Tung-Striebel smoother IEEE Trans. Autom. Control 53 845-9 (Pubitemid 351597197)
16. Shumway R H and Stoffer D S 2006 Time Series Analysis and Its Applications: With R Examples (Berlin: Springer)
17. Supp G G, Schlögl A, Trujillo-Barreto N, Müller M M and Gruber T 2007 Directed cortical information flow during human object recognition: analyzing induced EEG gamma-band responses in brain's source space PLOS ONE 2 e684
18. van der Merwe R 2004 Sigma-point Kalman filters for probability inference in dynamic state-space models PhD Thesis Oregon Health and Science University
19. van der Merwe R and Wan E 2003 Sigma-point Kalman filters for probabilistic inference in dynamic state-space models Proc. Workshop on Advances in Machine Learning