On the blind source separation of human electroencephalogram by approximate joint diagonalization of second order statistics

Clinical Neurophysiology

Volumn 119, Issue 12, 2008, Pages 2677-2686

  Congedo, Marco ^a   Gouy Pailler, Cédric ^a   Jutten, Christian ^a  

^a GIPSA LAB   (France)

Author keywords

Approximate joint diagonalization (AJD); Blind source separation (BSS); Electroencephalography (EEG); Fourier cospectra; Independent component analysis (ICA); Volume conduction

Indexed keywords

ARTIFACT; BRAIN SIZE; DIPOLE; ELECTROENCEPHALOGRAM; ELECTROENCEPHALOGRAPHY; FOURIER ANALYSIS; NEUROPHYSIOLOGY; PRIORITY JOURNAL; REVIEW; SCALP; STATISTICS; WAVEFORM;

ARTIFACTS; BRAIN; ELECTROENCEPHALOGRAPHY; HUMANS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; STATISTICS AS TOPIC;

EID: 56449125597     PISSN: 13882457     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.clinph.2008.09.007     Document Type: Review

References (126)

1. Aissa-El-Bey A., Linh-Trung N., Abed-Meraim K., Belouchrani A., and Grenier Y. Underdetermined blind separation of nondisjoint sources in the time-frequency domain. IEEE Trans Signal Process 55 3 (2007) 897-907
2. Anemüller J., Sejnowski T.J., and Makeig S. Complex independent component analysis of frequency-domain electroencephalographic data. Neural Netw 16 9 (2003) 1311-1323
3. Ans B, Hérault J, Jutten C. Adaptive neural architectures: detection of primitives. In: Proc COGNITIVA 1985. p. 593-597.
4. Barbati G., Sigismondi R., Zappasodi F., Porcaro C., Graziadio S., Valente G., et al. Functional source separation from magnetoencephalographic signals. Hum Brain Mapp 27 12 (2006) 925-934
5. Barbati G., Porcaro C., Hadjipapas A., Adjamian P., Pizzella V., Romani G.L., et al. Functional source separation applied to induced visual gamma activity. Hum Brain Mapp 29 2 (2008) 131-141
6. Bell A.J., and Sejnowski T.J. An information-maximization approach to blind separation and blind deconvolution. Neural Comput 7 (1995) 1129-1159
7. Belouchrani A., Abed-Meraim K., Cardoso J.-F., and Moulines E. A blind source separation technique using second-order statistics. IEEE Trans Signal Process 45 2 (1997) 434-444
8. Belouchrani A., and Amin M.G. Blind source separation based on time-frequency signal representations. IEEE Trans Signal Process 46 11 (1998) 2888-2897
9. Beran J. Statistics for long-memory processes (1994), Chapman & Hall, London
10. Bloomfield P. Fourier analysis of time series (2000), John Wiley & Sons, New York
11. Bousbia-Salah A., Belouchrani A., and Bousbia-Salah H. A one step time-frequency blind identification. 7th Int Symp Sig Process Appl 1 1 (2003) 581-584
12. Buzsáki G. Rhythms of the brain (2006), Oxford Univ Press, New York
13. Cao J., Murata N., Amari S.-I., Cichocki A., and Takeda T. Independent component analysis for an averaged single-trial MEG data decomposition and single-dipole localization. Neurocomputing 49 (2002) 255-277
14. Cardoso J.F., and Souloumiac A. Blind beamforming for non-Gaussian signals. IEE Proc-F (Radar and Signal Process) 140 6 (1993) 362-370
15. Cardoso J-F. On the performance of orthogonal source separation algorithms. In: Proc EUSIPCO, Edinburg (UK) 1994. p. 776-779.
16. Cardoso J.-F. Blind signal separation: statistical principles. IEEE Proc 9 10 (1998) 2009-2025
17. Cardoso J-F. Multidimensional independent component analysis. In: Proc ICASSP, Seattle, USA; p. 1998b. 1941-1944.
18. Cardoso J.-F. High-order contrasts for independent component analysis. Neural Comput 11 1 (1999) 157-192
19. Choi S., and Cichocki A. Blind separation of nonstationary sources in noisy mixtures. Electron Lett 36 (2000) 848-849
20. Choi S., Cichocki A., and Belouchrani. Second order nonstationary source separation. J VLSI Sig Process 32 1-2 (2002) 93-104
21. Choi S., Cichocki A., Park H.M., and Lee S.-Y. Blind source separation and independent component analysis: a review. Neural Inf Process Lett Rev 6 1 (2005) 1-57
22. Cichocki A., and Amari S.I. Adaptive blind signal and image processing. learning algorithms and applications (2002), John Wiley & Sons, New-York
23. Comon P. Independent Component Analysis, a new concept ?. Signal Process 36 3 (1994) 287-314
24. Congedo M. Subspace projection filters for real-time brain electromagnetic imaging. IEEE Trans Biomed Eng 53 8 (2006) 1624-1634
25. Cotter S., Rao B.D., Engan K., and Kreutz-Delgado K. Sparse solutions to linear inverse problems with multiple measurement vectors. IEEE Trans Signal Process 53 7 (2005) 2477-2488
26. Crespo-Garcia M., Atienza M., and Cantero J.L. Muscle artifact removal from human sleep EEG by using independent component analysis. Ann Biomed Eng 36 3 (2008) 467-475
27. Darmois G. Analyse générale des liaisons stochastiques. Rev Inst Inter Stat 21 (1953) 2-8
28. Dat T.H., and Guan C. Feature selection based on fisher ratio and mutual information analyses for robust brain computer interface. Proc ICASSP 1 (2007) I-337-I-340
29. De Clercq W., Vergult A., Vanrumste B., Van Paesschen W., and Van Huffel S. Canonical correlation analysis applied to remove muscle artifacts from the electroencephalogram. IEEE Trans Biomed Eng 53 12 Pt 1 (2006) 2583-2587
30. Dégerine S., and Malki R. Second-order blind separation of sources based on canonical partial innovations. IEEE Trans Signal Process 48 3 (2000) 629-641
31. Degerine S., and Kane E. A comparative study of approximate joint diagonalization algorithms for blind source separation in presence of additive noise. IEEE Trans Signal Process 55 6-2 (2007) 3022-3031
32. Deville Y. Temporal and time-frequency correlation-based blind source separation methods. In: Proc ICA2003, Nara, Japan; 2003. p. 1059-64.
33. Doron E, Yeredor A. Asymptotically Optimal Blind Separation of Parametric Gaussian Sources. In: Proc ICA 2004, Puntonet CG, Prieto A, editors. p. 390-97.
34. Dyrholm M., Makeig S., and Hansen L.K. Model selection for convolutive ICA with an application to spatiotemporal analysis of EEG. Neural Comput 19 4 (2007) 934-955
35. Fadaili E.M., Moreau N.T., and Moreau E. Nonorthogonal joint diagonalization/zero diagonalization for source separation based on time-frequency distributions. IEEE Trans Signal Process 55 5-1 (2007) 1673-1687
36. Féty L, Uffelen J-P. New methods for signal separation. In: Proc 14th conf HF Radio Syst Tech, London; 1988. p. 226-30.
37. Févotte C, Theis FJ. Pivot selection strategies in jacobi joint block-diagonalization. In: Proc. ICA, London, U.K 2007; 4666 of LNCS. p. 177-84.
38. Fitzgibbon S.P., Powers D.M., Pope K.J., and Clark C.R. Removal of EEG noise and artifact using blind source separation. J Clin Neurophysiol 24 3 (2007) 232-243
39. Frank R.M., and Frishkoff G.A. Automated protocol for evaluation of electromagnetic component separation (APECS): application of a framework for evaluating statistical methods of blink extraction from multichannel EEG. Clin Neurophysiol 118 1 (2007) 80-97
40. Frigo M., and Johnson S.G. The design and implementation of FFTW3. Proc IEEE 93 2 (2005) 216-231
41. Gasser T., Schuller J.C., and Gasser U.S. Correction of muscle artefacts in the EEG power spectrum. Clin Neurophysiol 116 9 (2005) 2044-2050
42. Gorodnitsky I.F., George J.S., and Rao B.D. Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm. Electroencephalogr Clin Neurophysiol 95 4 (1995) 231-251
43. Greenblatt R.E., Ossadtchi A., and Pflieger M.E. Local linear estimators for the bioelectromagnetic inverse problem. IEEE Trans Signal Process 53 9 (2005) 3403-3412
44. Gribonval R, Lesage S. A survey of Sparse Component Analysis for blind source separation: principles, perspectives, and new challenges. In: Proc. Eur Symp Artif Neural Netw (ESANN 2006) 2006. p. 323-30.
45. Guimaraes M.P., Wong D.K., Uy E.T., Grosenick L., and Suppes P. Single-trial classification of MEG recordings. IEEE Trans Biomed Eng 54 3 (2007) 436-443
46. Halder S., Bensch M., Mellinger J., Bogdan M., Kübler A., Birbaumer N., et al. Online artifact removal for brain-computer interfaces using support vector machines and blind source separation. Comput Intell Neurosci (2007) 82069
47. Hérault J, Jutten C. Space or time adaptive signal processing by neural network models. In: Proc Int Conf Neural Netw Comput, Snowbird (Utah), April 1986; vol. 151, p. 206-11.
48. Hesse C.W., and James C.J. On semi-blind source separation using spatial constraints with applications in EEG analysis. IEEE Trans Biomed Eng 53 12 (2006) 2525-2534
49. Hyvärinen A. Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans Neural Netw 10 3 (1999) 626-634
50. Hyvärinen A., Karhunen J., and Oja E. Independent component analysis (2001), John Wiley & Sons, New York
51. Ille N., Berg P., and Scherg M. Artifact correction of the ongoing EEG using spatial filters based on artifact and brain signal topographies. J Clin Neurophysiol 19 2 (2002) 113-124
52. Iriarte J., Urrestarazu E., Valencia M., Alegre M., Malanda A., Viteri C., et al. Independent component analysis as a tool to eliminate artifacts in EEG: a quantitative study. J Clin Neurophysiol 20 4 (2003) 249-257
53. James C., and Gibson O. Temporally constrained ICA: an application to artifact rejection in electromagnetic brain signal analysis. IEEE Trans Biomed Eng 50 9 (2003) 1108-1116
54. James C., and Hesse C. On the use of spectrally constrained ICA applied to single-channel ictal EEG recordings within a dynamical embedding framework. Conf Proc IEEE Eng Med Biol Soc 1 (2005) 659-956
55. Joyce C.A., Gorodnitsky I.F., and Kutas M. Automatic removal of eye movement and blink artifacts from EEG data using blind component separation. Psychophysiology 41 2 (2004) 313-325
56. Jung T.P., Makeig S., Westerfield M., Townsend J., Courchesne E., and Sejnowski T.J. Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects. Clin Neurophysiol 111 10 (2000) 1745-1758
57. Jutten C., and Herault J. Blind separation of sources, Part 1: an adaptive algorithm based on neuromimetic architecture. Signal Process 24 1 (1991) 1-10
58. Kachenoura A., Albera L., Senhadji L., and Comon P. ICA: a potential tool for BCI systems. IEEE signal Process Mag 25 1 (2008) 57-68
59. Kierkels J.J.M., van Boxtel G.J.M., and Vogten L.L.M. A model-based objective evaluation of eye movement correction in EEG recordings. IEEE Trans Biomed Eng 53 2 (2006) 246-253
60. Lee D.D., and Seung H.S. Learning the parts of objects by nonnegative matrix factorization. Nature 401 (1999) 788-791
61. Lee D.D., and Seung H.S. Algorithms for non-negative matrix factorization. Adv Neural Info Proc Syst 13 (2001) 556-562
62. Lemm S., Curio G., Hlushchuk Y., and Müller K.-R. Enhancing the signal-to-noise ratio of ICA-based extracted ERPs. IEEE Trans Biomed Eng 53 4 (2006) 601-607
63. Li X.-L., and Zhang X.-D. Nonorthogonal joint diagonalization free of degenerate solution. IEEE Trans Sig Proc 55 5 (2007) 1803-1814
64. Li Y., Cichocki A., and Amari S.-I. Blind estimation of channel parameters and source components for EEG signals: a sparse factorization approach. IEEE Trans Neural Netw 17 2 (2006) 419-431
65. Lopes da Silva F. Functional localization of brain sources using EEG and/or MEG data: volume conductor and source models. Magn Res Img 22 (2004) 1533-1538
66. Lopes da Silva F. Computer-assisted EEG diagnosis: pattern recognition and brain mapping. In: Niedermeyer E., and Lopes da Silva F. (Eds). Electroencephalography. Basic principles, clinical applications, and related fields. 5th ed. (2005), Lippincott Williams & Wilkins, New York 1233-1263
67. Lopes da Silva F. Event related potentials: methodology and quantification. In: Niedermeyer E., and Lopes da Silva F. (Eds). Electroencephalography. Basic principles, clinical applications, and related fields. 5th ed. (2005), Lippincott Williams & Wilkins, New York 991-1001
68. Lopes da Silva F., and Van Rotterdam A. Biophysical aspects of EEG and magnetoencephalogram generation. In: Niedermeyer E., and Lopes da Silva F. (Eds). Electroencephalography. Basic Principles, Clinical Applications, and Related Fields. 5th ed. (2005), Lippincott Williams & Wilkins, New York 107-125
69. Lu W., and Rajapaske J.C. Approach and applications of constrained ICA. IEEE Trans Neural Netw 16 1 (2005) 203-212
70. Matsuoka K., Ohya M., and Kawamoto M. A neural net for blind separation of nonstationary signals. Neural Netw 8 3 (1995) 411-419
71. Malmivuo J., and Plonsey R. Bioelectromagnetism. Principles and applications of bioelectric and biomagnetic fields (1995), Oxford Univ Press, New York
72. Mantini D., Perrucci M.G., DelGratta C., Romani G.L., and Corbetta M. Electrophisiological signatures of resting state networks in the human brain. PNAS 104 32 (2007) 10.1073
73. Meinecke F., Ziehe A., Kawanabe M., and Müller K.R. A resampling approach to estimate the stability of one- or multidimensional independent components. IEEE Trans Biomed Eng 49 (2002) 1514-1525
74. Molgedey L., and Schuster H.G. Separation of a mixture of independent signals using time delayed correlations. Phys Rev Lett 72 (1994) 3634-3636
75. Mosher J.C., Lewis P.S., and Leahy R.M. Multiple dipole modeling and localization from spatio-temporal MEGdata. IEEE Trans Biomed Eng 39 6 (1992) 541-557
76. Müller K.R., Vigario R., Meinecke F., and Ziehe A. Blind source separation techniques for decomposing event-related brain signals. Int J Bifurcat Chaos 14 2 (2004) 773-791
77. Niedermeyer E. The Normal EEG of the waking Adult. In: Niedermeyer E., and Lopes da Silva F. (Eds). Electroencephalography. Basic principles, clinical applications, and related fields. 5th ed. (2005), Lippincott Williams & Wilkins, New York 167-191
78. Niedermeyer E. Sleep and EEG. In: Electroencephalography. Basic principles, clinical applications, and related fields. Niedermeyer E, Lopes da Silva F, editors, 5th ed., New York: Lippincott Williams & Wilkins; 2005b. p. 193-207.
79. Niedermeyer E. Epileptic seizure disorders. In: Niedermeyer E., and Lopes da Silva F. (Eds). Electroencephalography. Basic principles, clinical applications, and related fields. 5th ed. (2005), Lippincott Williams & Wilkins, New York 505-619
80. Nunez P.L., and Srinivasan R. Electric field of the brain. 2nd ed. (2006), Oxford Univ Press, New York
81. Parra L., and Sajda P. Blind source separation via generalized eigenvalue decomposition. J Mach Learn Res 4 (2003) 1261-1269
82. Pham D.-T. Blind separation of instantaneous mixture of sources via the Gaussian mutual information criterion. Signal Process 81 (2001) 855-870
83. Pham D.-T. Joint approximate diagonalization of positive definite matrices. SIAM J Matrix Anal Appl 22 4 (2001) 1136-1152
84. Pham D.-T., and Cardoso J.-F. Blind separation of instantaneous mixtures of non stationary sources. IEEE Trans Signal Process 49 9 (2001) 1837-1848
85. Pham D.-T. Exploiting source non stationary and coloration in blind source separation. Digital Signal Process 1 (2002) 151-154
86. Phlypo R, Boon P, D'Asseler Y, Lemahieu I. Removing ocular movement artefacts by a joint smoothened subspace estimator. Comput Intell Neurosci 2007: ID 75079.
87. Pfurtscheller G., and Lopes da Silva F.H. Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin Neurophysiol 110 11 (1999) 1842-1857
88. Qin L., Ding L., and He B. Motor imagery classification by means of source analysis for brain-computer interface applications. J Neural Eng 1 (2004) 135-141
89. Roberts S. Independent component analysis: source assessment and separation, a Bayesian approach. IEE Proc Vis Image Signal Process 145 3 (1998) 149-154
90. Rodri{dotless}́guez-Rivera A., Baryshnikov B.V., Van Veen B.D., and Wakai R.T. MEG and EEG source localization in beamspace. IEEE Trans Biomed Eng 53 3 (2006) 430-441
91. Romero S., Mañanas M.A., and Barbanoj M.J. A comparative study of automatic techniques for ocular artifact reduction in spontaneous EEG signals based on clinical target variables: a simulation case. Comput Biol Med 38 3 (2008) 348-360
92. Sander T.H., Burghoff M., Curio G., and Trahms L. Single evoked somatosensory MEG responses extracted by time delayed decorrelation. IEEE Trans Signal process 53 9 (2005) 3384-3392
93. Särelä J., and Vigário R. Overlearning in marginal distribution-based ICA: analysis and solutions. J Mach Learn Res 4 (2003) 1447-1469
94. Sarvas J. Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem. Phys Med Biol 32 1 (1987) 11-22
95. Serby H., Yom-Tov E., and Inbar G.F. An improved P300-brain-computer interface. IEEE Trans Neural Syst Rehabil Eng 13 1 (2005) 89-98
96. Souloumiac A. Blind source detection and separation using second order nonstationarity. In: Proc ICASSP 1995. p. 1912-15.
97. Speckmann E.-J., and Elger C.E. Introduction to the neurophysiological basis of the EEG and DC potentials. In: Niedermeyer E., and Lopes da Silva F. (Eds). Electroencephalography. Basic principles, clinical applications, and related fields. 5th ed. (2005), Lippincott Williams & Wilkins, New York 17-29
98. Srinivasan R., Winter W.R., and Nunez P.L. Source analysis of EEG oscillations using high-resolution EEG and MEG. Prog Brain Res 159 (2006) 29-42
99. Steriade M. Cellular substrates of brain rhythms. In: Niedermeyer E., and Lopes da Silva F. (Eds). Electroencephalography. Basic principles, clinical applications, and related fields. 5th ed. (2005), Lippincott Williams & Wilkins, New York 31-83
100. Sutherland M.T., and Tang A.C. Reliable detection of bilateral activation in human primary somatosensory cortex by unilateral median nerve stimulation. Neuroimage 33 (2006) 1024-1054
101. Tang A.C., Sutherland M.T., and McKinney C.J. Validation of SOBI components from High-density EEG. Neuroimage 25 (2004) 539-553
102. Tang A.C., Liu J.-Y., and Sutherland M.T. Recovery of correlated neuronal sources from EEG: the good and bad ways of using SOBI. Neuroimage 28 (2005) 507-519
103. Tang A.C., Sutherland M.T., and Wang Y. Contrasting single-trial ERPs between experimental manipulations: improving differentiability by blind source separation. Neuroimage 29 (2006) 335-346
104. Theis F.J. Uniqueness of complex and multidimensional independent component analysis. Signal Process 84 (2004) 951-956
105. Theis FJ. Blind signal separation into groups of dependent signals using joint block diagonalization. In: Proc ISCAS, Kobe, Japan; 2005. p. 5878-81.
106. Theis FJ, Inouye Y. On the use of joint diagonalization in blind signal processing. In: Proc. ISCAS, Kos, Greece; 2006.
107. Thorpe S.G., Nunez P.L., and Srinivasan R. Identification of wave-like spatial structure in the SSVEP: comparison of simultaneous EEG and MEG. Stat Med 26 (2007) 3911-3926
108. Tichavski{dotless}́ P, Yeredor A, Nielsen J. A fast approximate joint diagonalization algorithm using a criterion with a block diagonal matrix. In: Proc ICASSP 2008, Las Vegas, USA; April 2008.
109. Tong L., Liu R.W., and Huang Y.-F. Blind Estimation of correlated source signals. Sig Syst Comput 1 (1990) 258-262
110. Tong L., Liu R.W., Soon V.C., and Huang Y.-F. Indeterminacy and identifiability of blind identification. IEEE Trans Circuits Syst 38 5 (1991) 499-509
111. Tong L., Soon V., Huang Y., and Liu R.W. A necessary and sufficient condition waveform-preserving blind estimation of multiple independent sources. IEEE Trans Signal Process 41 7 (1991) 2461-2470
112. Tong L., Inouye Y., and Liu R.W. Waveform-preserving blind estimation of multiple independent sources. IEEE Trans Signal Process 41 7 (1993) 2461-2470
113. Van Der Loo E., Congedo M., Plazier M., Van De Heyning P., and De Ridder D. Correlation between independent components of scalp EEG and intra-cranial EEG (iEEG) time series. Int J Bioelectromagnetism 9 4 (2007) 270-275
114. Vigário R.N. Extraction of ocular artifacts from EEG using independent component analysis. Electroenceph Clin Neurophysiol 103 (1997) 395-404
115. Vorobyov S., and Cichocki A. Blind noise reduction for multisensory signals using ICA and subspace filtering, with applications to EEG analysis. Biol Cybern 86 (2002) 293-303
116. Vollgraf R., and Obermayer K. Quadratic optimization for simultaneous matrix diagonalization. IEEE Trans Sig Process 54 9 (2006) 3270-3278
117. Wang S., and James C.J. Extracting rhythmic brain activity for brain-computer interfacing through constrained independent component analysis. Comput Intell Neurosci (2007) ID 41468
118. Wax M., and Sheinvald J. A least-squares approach to joint diagonalization. IEEE Signal Process Lett 4 2 (1997) 52-53
119. Whitham E.M., Pope K.J., Fitzgibbon S.P., Lewis T., Clark C.R., Loveless S., et al. Scalp electrical recording during paralysis: quantitative evidence that EEG frequencies above 20 Hz are contaminated by EMG. Clin Neurophysiol 118 8 (2007) 1877-1888
120. Yeredor A. Blind separation of Gaussian sources via second-order statistics with asymptotically optimal weighting. IEEE Signal Process Lett 7 7 (2000) 197-200
121. Yeredor A. Non-orthogonal joint diagonalization in the least-squares sense with application in blind source separation. IEEE Trans Signal Process 50 7 (2002) 1545-1553
122. Zhang Z.-L. Morphologically constrained ICA for extracting weak temporally correlated signals. Neurocomputing 71 (2008) 1669-1679
123. Zhang Y., and Amin M. Blind separation of nonstationary sources based on spatial time-frequency distributions. EURASIP J Appl Signal Process (2006) ID 64785
124. Zeman P.M., Till B.C., Livingston N.J., Tanaka J.W., and Driessen P.F. Independent component analysis and clustering improve signal-to-noise ratio for statistical analysis of event-related potentials. Clin Neurophysiol 118 12 (2007) 2591-2604
125. Ziehe A, Müller K-R. TDSEP-an efficient algorithm for blind separation using time structure. In: Proc Int Conf Artif Neural Netw (ICANN'98) 1998. p. 675-80.
126. Ziehe A., Laskov P., Nolte G., and Müller R.-K. A fast algorithm for joint diagonalization with non orthogonal transformations and its application to blind source separation. J Mach Learn Res 5 (2004) 777-800