Bayesian symmetrical EEG/fMRI fusion with spatially adaptive priors

NeuroImage

Volumn 55, Issue 1, 2011, Pages 113-132

  Luessi, Martin ^a   Babacan, S Derin ^b   Molina, Rafael ^c   Booth, James R ^d   Katsaggelos, Aggelos K ^a  

^a Northwestern University   (United States)

^b UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^c UNIVERSITY OF GRANADA   (Spain)

^d NORTHWESTERN UNIVERSITY   (United States)

Author keywords

M EEG source localization; Multimodal fusion; Spatial adaptivity; Total variation; Variational Bayes

Indexed keywords

ADAPTATION; ADULT; ALGORITHM; ARTICLE; BAYES THEOREM; BRAIN CORTEX; COMPUTER SIMULATION; CONTROLLED STUDY; ELECTROENCEPHALOGRAM; FACE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HEMODYNAMICS; HUMAN; HUMAN EXPERIMENT; MALE; NORMAL HUMAN; PATTERN RECOGNITION; PRIORITY JOURNAL;

ADULT; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; BRAIN MAPPING; ELECTROENCEPHALOGRAPHY; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE; VISUAL CORTEX; VISUAL PERCEPTION;

EID: 78951475125     PISSN: 10538119     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2010.11.037     Document Type: Article

References (56)

1. Adde G., Clerc M., Keriven R. Imaging methods for MEG/EEG inverse problem. International Journal of Bioelectromagnetism 2005, 7(2):111-114.
2. Ahlfors S.P., Simpson G.U. Geometrical interpretation of fMRI-guided MEG/EEG inverse estimates. Neuroimage 2004, 22(1):323-332. May.
3. Attias H. A variational Bayesian framework for graphical models. Advances in Neural Information Processing Systems 2000, 12(1-2):209-215.
4. Babacan S.D., Molina R., Katsaggelos A.K. Parameter estimation in TV image restoration using variational distribution approximation. IEEE Transactions on Image Processing 2008, 17(3):326-339.
5. Baillet S., Garnero L. A Bayesian approach to introducing anatomo-functional priors in the EEG/MEG inverse problem. IEEE Transactions on Biomedical Engineering 1997, 44(5):374-385. August.
6. Baillet S., Mosher J.C., Leahy R.M. Electromagnetic brain mapping. IEEE Signal Processing Magazine 2001, 18(6):14-30.
7. Bishop C.M. Pattern Recognition and Machine Learning 2006, Springer.
8. Brookings T., Ortigue S., Grafton S., Carlson J. Using ICA and realistic bold models to obtain joint EEG/fMRI solutions to the problem of source localization. Neuroimage 2009, 44(2):411-420. September.
9. Dale A.M., Sereno M.I. Improved localization of cortical activity by combining EEG and MEG with MRI cortical surface reconstruction: a linear approach. Journal of Cognitive Neuroscience 1993, 5:162-176.
10. Daunizeau J., Grova C., Mattout J., Marrelec G., Clonda D., Goulard B., Pelegrini-Issac M., Lina J.M., Benali H. Assessing the relevance of fMRI-based prior in the EEG inverse problem: a Bayesian model comparison approach. IEEE Transactions on Signal Processing 2005, 53(9):3461-3472.
11. Daunizeau J., Grova C., Marrelec G., Mattout J., Jbabdi S., Pelegrini-Issac M., Lina J.M., Benali H. Symmetrical event-related EEG/fMRI information fusion in a variational Bayesian framework. Neuroimage 2007, 36(1):69-87. May.
12. Frahm J., Bruhn H., Merboldt K.D., Math D. Dynamic MR imaging of human brain oxygenation during rest and photic stimulation. Journal of Magnetic Resonance Imaging 1992, 2(5):501-505.
13. Friedrich M., Friederici A.D. N400-like semantic incongruity effect in 19-month-olds: processing known words in picture contexts. Journal of Cognitive Neuroscience 2004, 16(8):1465-1477.
14. Friston K.J., Holmes A.P., Poline J.B., Grasby P.J., Williams S.C., Frackowiak R.S., Turner R. Analysis of fMRI time-series revisited. Neuroimage 1995, 2(1):45-53. March.
15. Friston K., Henson R., Phillips C., Mattout J. Bayesian estimation of evoked and induced responses. Human Brain Mapping 2006, 27(9):722-735.
16. Friston K.J., Harrison L., Daunizeau J., Kiebel S., Phillips C., Trujillo-Barreto N.J., Henson R., Flandin G., Mattout J. Multiple sparse priors for the M/EEG inverse problem. Neuroimage 2008, 39(3):1104-1120. February.
17. George J., Aine C., Mosher J., Schmidt D., Ranken D., Schlitt H., Wood C., Lewine J., Sanders J., Belliveau J. Mapping function in the human brain with magnetoencephalography, anatomical magnetic resonance imaging, and functional magnetic resonance imaging. Journal of Clinical Neurophysiology 1995, 12(5):406.
18. Grova C., Makni S., Flandin G., Ciuciu P., Gotman J., Poline J. Anatomically informed interpolation of fMRI data on the cortical surface. Neuroimage 2006, 31(4):1475-1486. July.
19. Hämäläinen M.S., Ilmoniemi R.J. Interpreting magnetic fields of the brain: minimum norm estimates. Medical & Biological Engineering & Computing 1994, 32(1):35-42.
20. Hämäläinen M., Hari R., Ilmoniemi R.J., Knuutila J., Lounasmaa O.V. Magnetoencephalography-theory, instrumentation, and applications to noninvasive studies of the working human brain. Reviews of Modern Physics 1993, 65(2):413-497. Apr.
21. Hardy G.H., Littlewood J.E., Pólya G. Inequalities 1988, Cambridge University Press.
22. Henson R.N., Goshen-Gottstein Y., Ganel T., Otten L.J., Quayle A., Rugg M.D. Electrophysiological and haemodynamic correlates of face perception, recognition and priming. Cerebral Cortex 2003, 13(7):793-805. July.
23. Henson R., Mattout J., Singh K., Barnes G., Hillebrand A., Friston K. Population-level inferences for distributed MEG source localization under multiple constraints: application to face-evoked fields. Neuroimage 2007, 38(3):422-438.
24. Henson, R. N., Flandin, G., Friston, K. J., Mattout, J., 2010. A parametric empirical Bayesian framework for fMRI-constrained MEG/EEG source reconstruction. Human Brain Mapping 31 (10), 1512-1531.
25. Hillyard S.A., Hinrichs H., Tempelmann C., Morgan S.T., Hansen J.C., Scheich H., Heinze H.J. Combining steady-state visual evoked potentials and fMRI to localize brain activity during selective attention. Human Brain Mapping 1997, 5(4):287-292.
26. Huang M.X., Dale A.M., Song T., Halgren E., Harrington D.L., Podgorny I., Canive J.M., Lewis S., Lee R.R. Vector-based spatial-temporal minimum L1-norm solution for MEG. Neuroimage 2006, 31(3):1025-1037.
27. Jaakkola T.S., Jordan M.I. Improving the mean field approximation via the use of mixture distributions. Learning in Graphical Models 1998, 89:163-173.
28. Jordan M.I., Ghahramani Z., Jaakkola T.S., Saul L.K. An introduction to variational methods for graphical models. Machine Learning 1999, 37(2):183-233.
29. Jun S.C., George J.S., Kim W., Paré-Blagoev J., Plis S., Ranken D.M., Schmidt D.M. Bayesian brain source imaging based on combined MEG/EEG and fMRI using MCMC. Neuroimage 2008, 40(4):1581-1594. May.
30. Lapalme E., Lina J., Mattout J. Data-driven parceling and entropic inference in MEG. Neuroimage 2006, 30(1):160-171. March.
31. Laufs H., Daunizeau J., Carmichael D.W., Kleinschmidt A. Recent advances in recording electrophysiological data simultaneously with magnetic resonance imaging. Neuroimage 2008, 40(2):515-528. April.
32. Liu Z., He B. fMRI-EEG integrated cortical source imaging by use of time-variant spatial constraints. Neuroimage 2008, 39(3):1198-1214. February.
33. Liu A.K., Belliveau J.W., Dale A.M. Spatiotemporal imaging of human brain activity using functional MRI constrained magnetoencephalography data: Monte Carlo simulations. Proceedings of the National Academy of Sciences U.S.A. 1998, 95(15):8945-8950. July.
34. MacKay D.J.C. Bayesian interpolation. Neural Computation 1992, 4(3):415-447.
35. Marrelec G., Benali H., Ciuciu P., Poline J.B. Bayesian estimation of the hemodynamic response function in functional MRI. Bayesian Inference and Maximum Entropy Methods in Science and Engineering 2002, 617(1):229-247.
36. Mattout J., Phillips C., Penny W.D., Rugg M.D., Friston K.J. Meg source localization under multiple constraints: an extended Bayesian framework. Neuroimage 2006, 30(3):753-767. April.
37. Ogawa S., Lee T., Kay A., Tank D. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proceedings of the National Academy of Sciences 1990, 87(24):9868.
38. Ou W., Nummenmaa A., Ahveninen J., Belliveau J.W., Hämäläinen M.S., Golland P. Multimodal functional imaging using fMRI-informed regional EEG/MEG source estimation. Neuroimage 2010, 52(1):97-108.
39. Parisi G. Statistical Field Theory 1998, Westview Press.
40. Pascual-Marqui R., Michela C.M., Lehmann D. Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. International Journal of Psychophysiology 1994, 18(1):49-65. October.
41. Pflieger M.E., Greenblatt R.E. Nonlinear analysis of multimodal dynamic brain imaging data. Int. J. Bioelectromagnetism 2001, 3.
42. Phillips C., Mattout J., Rugg M.D., Maquet P., Friston K.J. An empirical Bayesian solution to the source reconstruction problem in EEG. Neuroimage 2005, 24(4):997-1011. February.
43. Ramírez, R. R., May 2005. Neuromagnetic source imaging of spontaneous and evoked human brain dynamics. Ph.D. thesis, New York Univ., New York.
44. Rudin L.I., Osher S., Fatemi E. Nonlinear total variation based noise removal algorithms. Physica D 1992, 259-268.
45. Sanders L.D., Stevens C., Coch D., Neville H.J. Selective auditory attention in 3- to 5-year-old children: an event-related potential study. Neuropsychologia 2006, 44(11):2126-2138.
46. Sato M., Yoshioka T., Kajihara S., Toyama K., Goda N., Doya K., Kawato M. Hierarchical Bayesian estimation for MEG inverse problem. Neuroimage 2004, 23(3):806-826. November.
47. Scherg M., Von Cramon D. Evoked dipole source potentials of the human auditory cortex. Electroencephalography and Clinical Neurophysiology 1986, 65(5):344.
48. Strong D., Chan T. Edge-preserving and scale-dependent properties of total variation regularization. Inverse Problems 2003, 19:S165.
49. Thürmer G., Wuthrich C.A. Computing vertex normals from polygonal facets. Journal of Graphics Tools 1998, 3(1):43-46.
50. Tipping M.E. Sparse Bayesian learning and the relevance vector machine. Journal of Machine Learning Research 2001, 1:211-244.
51. Trujillo-Barreto N.J., Aubert-Vazquez E., Penny W.D. Bayesian M/EEG source reconstruction with spatio-temporal priors. Neuroimage 2008, 39(1):318-335. January.
52. Uutela K., Hämäläinen M., Somersalo E. Visualization of magnetoencephalographic data using minimum current estimates. Neuroimage 1999, 10(2):173-180.
53. Wipf, D. P., 2006. Bayesian methods for finding sparse representations. Ph.D. thesis, University of California, San Diego.
54. Wipf D.P., Nagarajan S.S. A unified Bayesian framework for MEG/EEG source imaging. Neuroimage 2009, 44(3):947-966.
55. Wipf D.P., Owen J.P., Attias H.T., Sekihara K., Nagarajan S.S. Robust Bayesian estimation of the location, orientation, and time course of multiple correlated neural sources using MEG. Neuroimage 2010, 49(1):641-655.
56. Yao J., Dewald J.P.A. Evaluation of different cortical source localization methods using simulated and experimental EEG data. Neuroimage 2005, 25(2):369-382. April.