EEG mapping and source imaging

Niedermeyer's Electroencephalography: Basic Principles, Clinical Applications, and Related Fields: Sixth Edition

Volumn , Issue , 2012, Pages 1179-1202

  Michel, Christoph M ^a   He, Bin ^b  

^a UNIVERSITY OF GENEVA   (Switzerland)

^b University of Minnesota   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84971430920     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Chapter

References (232)

1. Baillet S, Mosher JC, Leahy RM. Electromagnetic brain mapping. IEEE Signal Processing Mag. 2001;18:14-30.
2. He B, Lian J. High-resolution spatio-temporal functional neuroimaging of brain activity. Crit Rev Biomed Eng. 2002;30: 283-306.
3. Michel CM, Murray MM, Lantz G, et al. EEG source imaging. Clin Neurophysiol. 2004;115:2195-2222.
4. He B, Lian J. Electrophysiological neuroimaging: solving the EEG inverse problem. In: He B, ed. Neural Engineering. Norwell, MA: Kluwer Academic Publishers; 2005:221-261.
5. Sanei S, Chambers J. EEG Source localization. In: Sanei S, Chambers J, eds. EEG Signal Processing. New Jersey: Wiley; 2007:197-218.
6. Michel CM, Koenig T, Brandeis D, et al., eds. Electrical Neuroimaging. Cambridge, MA: Cambridge University Press; 2009.
7. Lehmann D. Multichannel topography of human alpha EEG fields. Electroencephalogr Clin Neurophysiol. 1971;31:439-449.
8. Lehmann D, Skrandies W. Reference-free identification of components of checkerboard-evoked multichannel potential fields. Electroencephalogr Clin Neurophysiol. 1980;48:609-621.
9. Lehmann D, Skrandies W. Spatial analysis of evoked potentials in man-a review. Prog Neurobiol. 1984;23:227-250.
10. Duffy FH, ed. Topographic Mapping of Brain Electrical Activity. Boston, MA: Butterworth; 1986.
11. Fender DH. Source localization of brain electrical activity. In: Gevins AS, Remont A, eds. Methods of Analysis of Brain Electrical and Magnetic Signals. Amsterdam: Elsevier; 1987:355-403.
12. Helmholtz HLP. Ueber einige gesetze der vertheilung elektrischer ströme in körperlichen leitern mit anwendung aud die thierischelektrischen versuche. Ann Phys Chem. 1853;9:211-233.
13. Michel CM, Brandeis D. Data acquisition and pre-processing standards for electrical neuroimaging. In: Michel CM, Koenig T, Brandeis D, et al., eds. Electrical Neuroimaging. Cambridge, MA: Cambridge University Press; 2009;79-92.
14. Tucker DM. Spatial sampling of head electrical fields: the geodesic sensor net. Electroencephalogr Clin Neurophysiol. 1993;87:154-163.
15. Michel CM, Lantz G, Spinelli L, et al. 128-Channel EEG source imaging in epilepsy: clinical yield and localization precision. J Clin Neurophysiol. 2004;21:71-83.
16. Russell GS, Jeffrey EK, Poolman P, et al. Geodesic photogrammetry for localizing sensor positions in dense-array EEG. Clin Neurophysiol. 2005;116:1130-1140.
17. Holmes MD. Dense array EEG: methodology and new hypothesis on epilepsy syndromes. Epilepsia. 2008;49:3-14.
18. Malmivuo JA, Suihko VE. Effect of skull resistivity on the spatial resolutions of EEG and MEG. IEEE Trans Biomed Eng. 2004;51: 1276-1280.
19. Li T-H, North G. Aliasing effects and sampling theorems of SRFs when sampled on a finite grid. Ann Inst Stat Math. 1996;49:341-354.
20. Grieve PG, Emerson RG, Isler JR, et al. Quantitative analysis of spatial sampling error in the infant and adult electroencephalogram. Neuroimage. 2004;21:1260-1274.
21. Srinivasan R, Nunez PL, Tucker DM, et al. Spatial sampling and filtering of EEG with spline Laplacians to estimate cortical potentials. Brain Topogr. 1996;8:355-366.
22. Srinivasan R, Tucker DM, Murias M. Estimating the spatial Nyquist of the human EEG. Behav Res Methods Instrum Comput. 1998;30:8-19.
23. Ryynänen OR, Hyttinen JA, Laarne PH, et al. Effect of electrode density and measurement noise on the spatial resolution of cortical potential distribution. IEEE Trans Biomed Eng. 2004;51:1547-1554.
24. Ryynänen OR, Hyttinen JA, Malmivuo JA. Effect of measurement noise and electrode density on the spatial resolution of cortical potential distribution with different resistivity values for the skull. IEEE Trans Biomed Eng. 2006;53:1851-1858.
25. Spitzer AR, Cohen LG, Fabrikant J, et al. A method for determining optimal interelectrode spacing for cerebral topographic mapping. Electroencephalogr Clin Neurophysiol. 1989;72:355-361.
26. Gevins A, Brickett P, Costales B, et al. Beyond topographic mapping: towards functional-anatomical imaging with 124-channel EEGs and 3-D MRIs. Brain Topogr. 1990;3:53-64.
27. Freeman WJ, Holmes MD, Burke BC, et al. Spatial spectra of scalp EEG and EMG from awake humans. Clin Neurophysiol. 2003;114: 1053-1068.
28. Lantz G, Grave de Peralta R, Spinelli L, et al. Epileptic source localization with high density EEG: how many electrodes are needed? Clin Neurophysiol. 2003;114:63-69.
29. Luu P, Tucker DM, Englander R, et al. Localizing acute stroke-related EEG changes: assessing the effects of spatial undersampling. J Clin Neurophysiol. 2001;18:302-317.
30. Rush S, Driscoll DA. EEG electrode sensitivity-an application of reciprocity. IEEE Trans Biomed Eng. 1969;16:15-22.
31. Oostendorp TF, Delbeke J, Stegeman DF. The conductivity of the human skull: results of in vivo and in vitro measurements. IEEE Trans Biomed Eng. 2000;47:1487-1492.
32. Hoekema R, Wieneke GH, Leijten FS, et al. Measurement of the conductivity of skull, temporarily removed during epilepsy surgery. Brain Topogr. 2003;16:29-38.
33. Lai Y, van Drongelen W, Ding L, et al. Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra- and intra-cranial electrical potential recordings. Clin Neurophysiol. 2005;116:456-465.
34. Goncalves S, de Munck JC, Verbunt JP, et al. In vivo measurement of the brain and skull resistivities using an EIT-based method and the combined analysis of SEF/SEP data. IEEE Trans Biomed Eng. 2003;50:1124-1128.
35. Zhang Y, van Drongelen W, He B. Estimation of in vivo brain-to-skull conductivity ratio in humans. Appl Phys Lett. 2006;89: 223903-223905.
36. Fifer WP, Grieve PG, Grose-Fifer J, et al. High-density electroencephalogram monitoring in the neonate. Clin Perinatol. 2006;33:679-691, vii.
37. Zhang X, van Drongelen W, Hecox KE, et al. High-resolution EEG: cortical potential imaging of interictal spikes. Clin Neurophysiol. 2003;114:1963-1973.
38. Ding L, Worrell GA, Lagerlund TD, et al. 3D source localization of interictal spikes in epilepsy patients with MRI lesions. Phys Med Biol. 2006;51:4047-4062.
39. Sperli F, Spinelli L, Seeck M, et al. EEG source imaging in paediatric epilepsy surgery: a new perspective in presurgical workup. Epilepsia. 2006;47:981-990.
40. Ding L, Worrell GA, Lagerlund TD, et al. Ictal source analysis: localization and imaging of causal interactions in humans. Neuroimage. 2007;34:575-586.
41. Ferree TC, Eriksen KJ, Tucker DM. Regional head tissue conductivity estimation for improved EEG analysis. IEEE Trans Biomed Eng. 2000;47:1584-1592.
42. Gao N, Zhu SA, He B. Estimation of electrical conductivity distribution within the human head from magnetic flux density measurement. Phys Med Biol. 2005;50:2675-2687.
43. Yuval-Greenberg S, Tomer O, Keren AS, et al. Transient induced gamma-band response in EEG as a manifestation of miniature saccades. Neuron. 2008;58:429-441.
44. Perrin F, Pernier J, Bertrand O, et al. Spherical splines for scalp potential and current density mapping. Electroencephalogr Clin Neurophysiol. 1989;72:184-187.
45. Fletcher EM, Kussmaul CL, Mangun GR. Estimation of interpolation errors in scalp topographic mapping. Electroencephalogr Clin Neurophysiol. 1996;98:422-434.
46. Jung TP, Makeig S, Humphries C, et al. Removing electroencephalographic artifacts by blind source separation. Psychophysiology. 2000;37:163-178.
47. Desmedt JE, Tomberg C, Noel P, et al. Beware of the average reference in brain mapping. Electroencephalogr Clin Neurophysiol Suppl. 1990;41:22-27.
48. Tomberg C, Noel P, Ozaki I, et al. Inadequacy of the average reference for the topographic mapping of focal enhancements of brain potentials. Electroencephalogr Clin Neurophysiol. 1990;77: 259-265.
49. Pascual-Marqui RD, Lehmann D. Comparison of topographic maps and the reference electrode: comments on two papers by Desmedt and collaborators. Electroencephalogr Clin Neurophysiol. 1993;88:530-531, 534-536.
50. Pascual-Marqui RD, Lehmann D. Topographic maps, source localization inference, and the reference electrode: comments on a paper by Desmedt et al. Electroencephalogr Clin Neurophysiol. 1993;88: 532-536.
51. Junghofer M, Elbert T, Tucker DM, et al. The polar average reference effect: a bias in estimating the head surface integral in EEG recording. Clin Neurophysiol. 1999;110:1149-1155.
52. Lehmann D, Skrandies W. Reference-free identification of components of checkerboard-evoked multichannel potential fields. Electroencephalogr Clin Neurophysiol. 1980;48:609-621.
53. Geselowitz DB. The zero of potential. IEEE Eng Med Biol Mag. 1998;17:128-132.
54. Murray MM, Brunet D, Michel CM. Topographic ERP analyses: a step-by-step tutorial review. Brain Topogr. 2008;20:249-264.
55. Perrin F, Pernier J, Bertrand O, et al. Mapping of scalp potentials by surface spline interpolation. Electroencephalogr Clin Neurophysiol. 1987;66:75-81.
56. Nunez PL, Silberstein RB, Cadusch PJ, et al. A theoretical and experimental study of high resolution EEG based on surface Laplacians and cortical imaging. Electroencephalogr Clin Neurophysiol. 1994;90:40-57.
57. Hjorth B. An on-line transformation of EEG scalp potentials into orthogonal source derivations. Electroencephalogr Clin Neurophysiol. 1975;39:526-530.
58. Perrin F, Bertrand O, Pernier J. Scalp current density mapping: value and estimation from potential data. IEEE Trans Biomed Eng. 1987;34:283-288.
59. He B, Lian J, Li G. High-resolution EEG: a new realistic geometry spline Laplacian estimation technique. Clin Neurophysiol. 2001;112: 845-852.
60. Nunez PL, Srinivasan R. Electric Fields of the Brain: The Neurophysics of EEG. 2nd ed. New York: Oxford University Press; 2006.
61. Skrandies W. The effect of stimulation frequency and retinal stimulus location on visual evoked potential topography. Brain Topogr. 2007;20:15-20.
62. Brandeis D, Naylor H, Halliday R, et al. Scopolamine effects on visual information processing, attention, and event-related potential map latencies. Psychophysiology. 1992;29:315-336.
63. Vaughan HGJ. The neural origins of human event-related potentials. Ann N Y Acad Sci. 1982;388:125-138.
64. Picton TW, Bentin S, Berg P, et al. Guidelines for using human event-related potentials to study cognition: recording standards and publication criteria. Psychophysiology. 2000;37:127-152.
65. Koenig T, Wackermann J. Overview of analytical approaches. In: Michel CM, Koenig T, Brandeis D, et al., eds. Electrical Neuroimaging. Cambridge, MA: Cambridge University Press; 2009:93-109.
66. Skrandies W. Data reduction of multichannel fields: global field power and principal component analysis. Brain Topogr. 1989;2: 73-80.
67. John ER, Easton P, Prichep LS, et al. Standardized varimax descriptors of event related potentials: basic considerations. Brain Topogr. 1993;6:143-162.
68. Wackermann J. Beyond mapping: estimating complexity of multichannel EEG recordings. Acta Neurobiol Exp (Wars). 1996;56: 197-208.
69. Kayser J, Tenke CE. Trusting in or breaking with convention: towards a renaissance of principal components analysis in electro-physiology. Clin Neurophysiol. 2005;116:1747-1753.
70. Spencer KM, Dien J, Donchin E. Spatiotemporal analysis of the late ERP responses to deviant stimuli. Psychophysiology. 2001;38: 343-358.
71. Kayser J, Tenke CE. Optimizing PCA methodology for ERP component identification and measurement: theoretical rationale and empirical evaluation. Clin Neurophysiol. 2003;114:2307-2325.
72. Kayser J, Tenke CE. Principal components analysis of Laplacian waveforms as a generic method for identifying ERP generator patterns: II. Adequacy of low-density estimates. Clin Neurophysiol. 2006;117:369-380.
73. Pourtois G, Deplanque S, Michel C, et al. Beyond the conventional event-related brain potential (ERP): exploring the time-course of visual emotion processing using topographic and principal component analyses. Brain Topogr. 2008;20:265-277.
74. Makeig S, Jung TP, Bell AJ, et al. Blind separation of auditory event-related brain responses into independent components. Proc Natl Acad Sci U S A. 1997;94:10979-10984.
75. Benar C, Aghakhani Y, Wang Y, et al. Quality of EEG in simultaneous EEG-fMRI for epilepsy. Clin Neurophysiol. 2003;114:569-580.
76. Briselli E, Garreffa G, Bianchi L, et al. An independent component analysis-based approach on ballistocardiogram artifact removing. Magn Reson Imaging. 2006;24:393-400.
77. Mantini D, Perrucci MG, Cugini S, et al. Complete artifact removal for EEG recorded during continuous fMRI using independent component analysis. Neuroimage. 2007;34:598-607.
78. Debener S, Strobel A, Sorger B, et al. Improved quality of auditory event-related potentials recorded simultaneously with 3-T fMRI: removal of the ballistocardiogram artefact. Neuroimage. 2007;34: 587-597.
79. Grouiller F, Vercueil L, Krainik A, et al. A comparative study of different artefact removal algorithms for EEG signals acquired during functional MRI. Neuroimage. 2007;38:124-137.
80. Debener S, Mullinger KJ, Niazy RK, et al. Properties of the ballistocardiogram artefact as revealed by EEG recordings at 1.5, 3 and 7 T static magnetic field strength. Int J Psychophysiol. 2008;67:189-199.
81. Makeig S, Westerfield M, Townsend J, et al. Functionally independent components of early event-related potentials in a visual spatial attention task. Philos Trans R Soc Lond B Biol Sci. 1999;354:1135-1144.
82. Lehmann D, Ozaki H, Pal I. EEG alpha map series: brain micro-states by space-oriented adaptive segmentation. Electroencephalogr Clin Neurophysiol. 1987;67:271-288.
83. Lehmann D. Brain electric fields and brain functional states. In: Friedrich R, Wunderlin A, eds. Evolution of Dynamical Structures in Complex Systems. Berlin: Springer; 1992:235-248.
84. Strik WK, Lehmann D. Data determined window size and space-oriented segmentation of spontaneous EEG map series. Electroencephalogr Clin Neurophysiol. 1993;87:169-174.
85. Wackerman J, Lehmann D, Michel CM, et al. Adaptive segmentation of spontaneous EEG map series into spatially defined microstates. Int J Psychophysiol. 1993;14:269-283.
86. Koenig T, Prichep L, Lehmann D, et al. Millisecond by millisecond, year by year: normative EEG microstates and developmental stages. Neuroimage. 2002;16:41-48.
87. Pascual-Marqui RD, Michel CM, Lehmann D. Segmentation of brain electrical activity into microstates: model estimation and validation. IEEE Trans Biomed Eng. 1995;42:658-665.
88. Lehmann D, Pascual-Marqui R, Michel CM. EEG microstates. Scholarpedia. 2009;4:7632.
89. Baars BJ. The conscious access hypothesis: origins and recent evidence. Trends Cogn Sci. 2002;6:47-52.
90. Dehaene S, Sergent C, Changeux JP. A neuronal network model linking subjective reports and objective physiological data during conscious perception. Proc Natl Acad Sci U S A. 2003;100:8520-8525.
91. Grossberg S. The complementary brain: unifying brain dynamics and modularity. Trends Cogn Sci. 2000;4:233-246.
92. Bressler SL, Tognoli E. Operational principles of neurocognitive networks. Int J Psychophysiol. 2006;60:139-148.
93. Fingelkurts AA. Timing in cognition and EEG brain dynamics: discreteness versus continuity. Cogn Process. 2006;7:135-162.
94. Strik WK, Dierks T, Becker T, et al. Larger topographical variance and decreased duration of brain electric microstates in depression. J Neural Transm Gen Sect. 1995;99:213-222.
95. Strik WK, Chiaramonti R, Muscas GC, et al. Decreased EEG microstate duration and anteriorisation of the brain electrical fields in mild and moderate dementia of the Alzheimer type. Psychiatry Res. 1997;75:183-191.
96. Koenig T, Prichep L, Dierks T, et al. Decreased EEG synchronization in Alzheimer's disease and mild cognitive impairment. Neurobiol Aging. 2005;26:165-171.
97. Koenig T, Lehmann D, Merlo MC, et al. A deviant EEG brain microstate in acute, neurolepticnaive schizophrenics at rest. Eur Arch Psychiatry Clin Neurosci. 1999;249:205-211.
98. Lehmann D, Faber PL, Galderisi S, et al. EEG microstate duration and syntax in acute, medication-naive, first-episode schizophrenia: a multi-center study. Psychiatry Res. 2005;138:141-156.
99. Lantz G, Michel CM, Seeck M, et al. Space-oriented segmentation and 3-dimensional source reconstruction of ictal EEG patterns. Clin Neurophysiol. 2001;112:688-697.
100. Lehmann D, Wackermann J, Michel CM, et al. Space-oriented EEG segmentation reveals changes in brain electric field maps under the influence of a nootropic drug. Psychiatry Res. 1993;50:275-282.
101. Kinoshita T, Strik WK, Michel CM, et al. Microstate segmentation of spontaneous multichannel EEG map series under diazepam and sulpiride. Pharmacopsychiatry. 1995;28:51-55.
102. Michel CM, Grave de Peralta R, Lantz G, et al. Spatio-temporal EEG analysis and distributed source estimation in presurgical epilepsy evaluation. J Clin Neurophysiol. 1999;16:225-238.
103. Michel CM, Thut G, Morand S, et al. Electric source imaging of human brain functions. Brain Res Brain Res Rev. 2001;36: 108-118.
104. Pegna AJ, Khateb A, Spinelli L, et al. Unravelling the cerebral dynamics of mental imagery. Hum Brain Mapp. 1997;5:410-421.
105. Arzy S, Mohr C, Michel CM, et al. Duration and not strength of activation in temporo-parietal cortex positively correlates with schizotypy. Neuroimage. 2007;35:326-333.
106. Lascano AM, Brodbeck V, Lalive PH, et al. Increasing the diagnostic value of evoked potentials in multiple sclerosis by quantitative topographic analysis of multichannel recordings. J Clin Neurophysiol. 2009;26:316-325.
107. Murray MM, Michel CM, Grave de Peralta R, et al. Rapid discrimination of visual and multisensory memories revealed by electrical neuroimaging. Neuroimage. 2004;21:125-135.
108. Ortigue S, Michel CM, Murray MM, et al. Electrical neuroimaging reveals early generator modulation to emotional words. Neuroimage. 2004;21:1242-1251.
109. Overney LS, Michel CM, Harris IM, et al. Cerebral processes in mental transformations of body parts: recognition prior to rotation. Brain Res Cogn Brain Res. 2005;25:722-734.
110. Murray MM, Camen C, Gonzalez Andino SL, et al. Rapid brain discrimination of sounds of objects. J Neurosci. 2006;26:1293-1302.
111. De Santis L, Spierer L, Clarke S, et al. Getting in touch: segregated somatosensory what and where pathways in humans revealed by electrical neuroimaging. Neuroimage. 2007;37:890-903.
112. Schnider A, Mohr C, Morand S, et al. Early cortical response to behaviorally relevant absence of anticipated outcomes: a human event-related potential study. Neuroimage. 2007;35:1348-1355.
113. Thierry G, Martin CD, Downing P, et al. Controlling for inter-stimulus perceptual variance abolishes N170 face selectivity. Nat Neurosci. 2007;10:505-511.
114. Arzy S, Molnar-Szakacs I, Blanke O. Self in time: imagined self-location influences neural activity related to mental time travel. J Neurosci. 2008;28:6502-6507.
115. Spierer L, Murray MM, Tardif E, et al. The path to success in auditory spatial discrimination: electrical neuroimaging responses within the supratemporal plane predict performance outcome. Neuroimage. 2008;41:493-503.
116. Kavanagh RN, Darcey TM, Lehmann D, et al. Evaluation of methods for three-dimensional localization of electrical sources in the human brain. IEEE Trans Biomed Eng. 1978;25:421-429.
117. Scherg M, von Cramon D. A new interpretation of the generators of BAEP waves I-V: results of a spatio-temporal dipole model. Electroencephalogr Clin Neurophysiol. 1985;62:290-299.
118. He B, Musha T, Okamoto Y, et al. Electric dipole tracing in the brain by means of the boundary element method and its accuracy. IEEE Trans Biomed Eng. 1987;34:406-414.
119. Cuffin BN, Cohen D, Yunokuchi K, et al. Tests of EEG localization accuracy using implanted sources in the human brain. Ann Neurol. 1991;29:132-138.
120. Cuffin BN. A method for localizing EEG sources in realistic head models. IEEE Trans Biomed Eng. 1995;42:68-71.
121. Nolte G, Curio G. Current multipole expansion to estimate lateral extent of neuronal activity: a theoretical analysis. IEEE Trans Biomed Eng. 2000;47:1347-1355.
122. Jerbi K, Baillet S, Mosher JC, et al. Localization of realistic cortical activity in MEG using current multipoles. Neuroimage. 2004;22: 779-793.
123. Pascual-Marqui RD, Michel CM, Lehmann D. Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. Int J Psychophysiol. 1994;18:49-65.
124. Dale AM, Sereno MI. Improved localization of cortical activity by combining EEG and MEG with MRI cortical surface reconstruction: a linear approach. J Cogn Neurosci. 1993;5:162-176.
125. He B, Yao D, Lian J, et al. An equivalent current source model and Laplacian weighted minimum norm current estimates of brain electrical activity. IEEE Trans Biomed Eng. 2002;49:277-288.
126. Grave de Peralta Menendez R, Gonzalez Andino SL, Morand S, et al. Imaging the electrical activity of the brain: ELECTRA. Hum Brain Mapp. 2000;9:1-12.
127. Plonsey R. Bioelectric Phenomena. New York, NY: McGraw-Hill; 1969.
128. Wilson FN, Bayley RH. The electric field of an eccentric dipole in a homogeneous spherical conducting medium. Circulation. 1950;1:84-92.
129. Wang Y, He B. A computer simulation study of cortical imaging from scalp potentials. IEEE Trans Biomed Eng. 1998;45:724-735.
130. Cuffin BN, Cohen D. Comparison of the magnetoencephalogram and electroencephalogram. Electroencephalogr Clin Neurophysiol. 1979;47:132-146.
131. Sun M. An efficient algorithm for computing multishell spherical volume conductor models in EEG dipole source localization. IEEE Trans Biomed Eng. 1997;44:1243-1252.
132. Spinelli L, Andino SG, Lantz G, et al. Electromagnetic inverse solutions in anatomically constrained spherical head models. Brain Topogr. 2000;13:115-125.
133. Hämäläinen M, Sarvas J. Realistic conductor geometry model of the human head for interpretation of neuromagnetic data. IEEE Trans Biomed Eng. 1989;36:165-171.
134. Meijs JW, Weier OW, Peters MJ, et al. On the numerical accuracy of the boundary element method. IEEE Trans Biomed Eng. 1989;36:1038-1049.
135. Yan Y, Nunez PL, Hart RT. Finite-element model of human head: scalp potentials due to dipole sources. Med Biol Eng Comput. 1991;29:475-481.
136. Zhang YC, Zhu SA, He B. A second-order finite element algorithm for solving the three-dimensional EEG forward problem. Phys Med Biol. 2004;49:2975-2987.
137. Wolters CH, Anwander A, Tricoche X, et al. Influence of tissue conductivity anisotropy on EEG/MEG field and return current computation in a realistic head model: a simulation and visualization study using high-resolution finite element modeling. Neuroimage. 2006;30:813-826.
138. Zhang Y, Ding L, van Drongelen W, et al. A cortical potential imaging study from simultaneous extra- and intracranial electrical recordings by means of the finite element method. Neuroimage. 2006;31:1513-1524.
139. Zhang Y, van Drongelen W, Kohrman M, et al. Three-dimensional brain current source reconstruction from intra-cranial ECoG recordings. Neuroimage. 2008;42:683-695.
140. Lee WH, Liu Z, Mueller BA, et al. Influence of white matter anisotropic conductivity on EEG source localization: comparison to fMRI in human primary visual cortex. Clin Neurophysiol. 2009;120:2071-2081.
141. Withey DJ, Koles ZJ. A review of medical image segmentation: methods and available software. Int J Bioelectromagnetism. 2008;10:125-148.
142. Basser PJ, Mattiello J, LeBihan D. MR diffusion tensor spectroscopy and imaging. Biophys J. 1994;66:259-267.
143. Tuch DS, Wedeen VJ, Dale AM, et al. Conductivity tensor mapping of the human brain using diffusion tensor MRI. Proc Natl Acad Sci U S A. 2001;98:11697-11701.
144. Wang K, Zhu S, Mueller BA, et al. A new method to derive white matter conductivity from diffusion tensor MRI. IEEE Trans Biomed Eng. 2008;55:2481-2486.
145. Homma S, Musha T, Nakajima Y, et al. Location of electric current sources in the human brain estimated by the dipole tracing method of the scalp-skull-brain (SSB) head model. Electroencephalogr Clin Neurophysiol. 1994;91:374-382.
146. Roth BJ, Ko D, von Albertini-Carletti IR, et al. Dipole localization in patients with epilepsy using the realistically shaped head model. Electroencephalogr Clin Neurophysiol. 1997;102:159-166.
147. Bai X, Towle VL, He EJ, et al. Evaluation of cortical imaging techniques based on somatosensory evoked potentials. Conf Proc IEEE Eng Med Biol Soc. 2006;1:1000-1001.
148. Diekmann V, Becker W, Jurgens R, et al. Localisation of epileptic foci with electric, magnetic and combined electromagnetic models. Electroencephalogr Clin Neurophysiol. 1998;106:297-313.
149. Fuchs M, Wagner M, Wischmann HA, et al. Improving source reconstructions by combining bioelectric and biomagnetic data. Electroencephalogr Clin Neurophysiol. 1998;107:93-111.
150. Fletcher DJ, Amir A, Jewett DL, et al. Improved method for computation of potentials in a realistic head shape model. IEEE Trans Biomed Eng. 1995;42:1094-1104.
151. Bai X, He B. Estimation of number of independent brain electric sources from the scalp EEGs. IEEE Trans Biomed Eng. 2006;53: 1883-1892.
152. Ebersole JS. Non-invasive localization of the epileptogenic focus by EEG dipole modeling. Acta Neurol Scand Suppl. 1994;152:20-28.
153. Lantz G, Ryding E, Rosén I. Three dimensional localisation of interictal epileptiform activity with dipole analysis: comparison with intracranial recordings and SPECT findings. J Epilepsy. 1994;7:117-129.
154. Ebersole JS, Hawes-Ebersole S. Clinical application of dipole models in the localization of epileptiform activity. J Clin Neurophysiol. 2007;24:120-129.
155. Cuffin BN. EEG localization accuracy improvements using realistically shaped head models. IEEE Trans Biomed Eng. 1996;43: 299-303.
156. Waberski TD, Buchner H, Lehnertz K, et al. Properties of advanced headmodelling and source reconstruction for the localization of epileptiform activity. Brain Topogr. 1998;10:283-290.
157. Benar CG, Gotman J. Modeling of post-surgical brain and skull defects in the EEG inverse problem with the boundary element method. Clin Neurophysiol. 2002;113:48-56.
158. Martinez A, Anllo-Vento L, Sereno MI, et al. Involvement of striate and extrastriate visual cortical areas in spatial attention. Nat Neurosci. 1999;2:364-369.
159. Northoff G, Richter A, Gessner M, et al. Functional dissociation between medial and lateral prefrontal cortical spatiotemporal activation in negative and positive emotions: a combined fMRI/MEG study. Cereb Cortex. 2000;10:93-107.
160. Lantz G, Holub M, Ryding E, et al. Simultaneous intracranial and extracranial recording of interictal epileptiform activity in patients with drug resistant partial epilepsy: patterns of conduction and results from dipole reconstructions. Electroencephalogr Clin Neurophysiol. 1996;99:69-78.
161. Huppertz HJ, Hof E, Klisch J, et al. Localization of interictal delta and epileptiform EEG activity associated with focal epileptogenic brain lesions. Neuroimage. 2001;13:15-28.
162. Cakmur R, Towle VL, Mullan JF, et al. Intra-operative localization of sensorimotor cortex by cortical somatosensory evoked potentials: from analysis of waveforms to dipole source modeling. Acta Neurochir (Wien). 1997;139:1117-1124 [discussion 1115-1124].
163. Mine S, Oka N, Yamaura A, et al. Presurgical functional localization of primary somatosensory cortex by dipole tracing method of scalp-skull-brain head model applied to somatosensory evoked potential. Electroencephalogr Clin Neurophysiol. 1998;108:226-233.
164. Mosher JC, Lewis PS, Leahy RM. Multiple dipole modeling and localization from spatio-temporal MEG data. IEEE Trans Biomed Eng. 1992;39:541-557.
165. Sekihara K, Poeppel D, Marantz A, et al. Noise covariance incorporated MEG-MUSIC algorithm: a method for multiple-dipole estimation tolerant of the influence of background brain activity. IEEE Trans Biomed Eng. 1997;44:839-847.
166. Mosher JC, Leahy RM. Source localization using recursively applied and projected (RAP) MUSIC. IEEE Trans Signal Process. 1999;47:332-340.
167. Xu XL, Xu B, He B. An alternative subspace approach to EEG dipole source localization. Phys Med Biol. 2004;49:327-343.
168. Ding L, He B. Spatio-temporal EEG source localization using a three-dimensional subspace FINE approach in a realistic geometry inhomogeneous head model. IEEE Trans Biomed Eng. 2006;53:1732-1739.
169. Ding L, Zhang N, Chen W, et al. Three-dimensional imaging of complex neural activation in humans from EEG. IEEE Trans Biomed Eng. 2009;56:1980-1988.
170. van Veen BD, van Drongelen W, Yuchtman M, et al. Localization of brain electrical activity via linearly constrained minimum variance spatial filtering. IEEE Trans Biomed Eng. 1997;44:867-880.
171. Sekihara K, Nagarajan SS, Poeppel D, et al. Reconstructing spatio-temporal activities of neural sources using an MEG vector beam-former technique. IEEE Trans Biomed Eng. 2001;48:760-771.
172. Grave de Peralta R, Gonzalez S, Lantz G, et al. Noninvasive localization of electromagnetic epileptic activity. I. Method descriptions and simulations. Brain Topogr. 2001;14:131-137.
173. Lantz G, Spinelli L, Menendez RG, et al. Localization of distributed sources and comparison with functional MRI. Epileptic Disord. 2001; (special issue):45-58.
174. Lantz G, Spinelli L, Seeck M, et al. Propagation of interictal epileptiform activity can lead to erroneous source localizations: a 128 channel EEG mapping study. J Clin Neurophysiol. 2003;20:311-319.
175. Hämäläinen MS, Ilmoniemi RJ. Interpreting measured magnetic fields of the brain: estimation of current distributions. Helsinki: Helsinki University of Technology; 1984:28 pp.
176. Wang JZ, Williamson SJ, Kaufman L. Magnetic source images determined by a lead-field analysis: the unique minimum-norm least-squares estimation. IEEE Trans Biomed Eng. 1992;39:665-675.
177. Grave de Peralta Menendez R, Murray MM, Michel CM, et al. Electrical neuroimaging based on biophysical constraints. Neuroimage. 2004;21:527-539.
178. Dale AM, Liu AK, Fischl BR, et al. Dynamic statistical parametric mapping: combining fMRI and MEG for high-resolution imaging of cortical activity. Neuron. 2000;26:55-67.
179. Pascual-Marqui RD, Esslen M, Kochi K, et al. Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review. Methods Find Exp Clin Pharmacol. 2002;24(suppl C):91-95.
180. Pascual Marqui RD, Sekihara K, Brandeis D, et al. Imaging the electrical neuronal generators of EEG/MEG. In: Michel CM, Koenig T, Brandeis D, et al., eds. Electrical Neuroimaging. Cambridge, MA: Cambridge University Press; 2009;49-78.
181. Gorodnitsky IF, George JS, Rao BD. Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm. Electroencephalogr Clin Neurophysiol. 1995;95:231-251.
182. Yao D, He B. A self-coherence enhancement algorithm and its application to enhancing three-dimensional source estimation from EEGs. Ann Biomed Eng. 2001;29:1019-1027.
183. Matsuura K, Okabe Y. Selective minimum-norm solution of the biomagnetic inverse problem. IEEE Trans Biomed Eng. 1995;42: 608-615.
184. Uutela K, Hamalainen M, Somersalo E. Visualization of magnetoencephalographic data using minimum current estimates. Neuroimage. 1999;10:173-180.
185. Huang MX, Dale AM, Song T, et al. Vector-based spatial-temporal minimum L1-norm solution for MEG. Neuroimage. 2006;31:1025-1037.
186. Ding L, He B. Sparse source imaging in electroencephalography with accurate field modeling. Hum Brain Mapp. 2008;29: 1053-1067.
187. Sidman RD, Vincent DJ, Smith DB, et al. Experimental tests of the cortical imaging technique-applications to the response to median nerve stimulation and the localization of epileptiform discharges. IEEE Trans Biomed Eng. 1992;39:437-444.
188. Le J, Gevins A. Method to reduce blur distortion from EEG's using a realistic head model. IEEE Trans Biomed Eng. 1993;40:517-528.
189. Srebro R, Oguz RM, Hughlett K, et al. Estimating regional brain activity from evoked potential fields on the scalp. IEEE Trans Biomed Eng. 1993;40:509-516.
190. Gevins A, Le J, Martin NK, et al. High resolution EEG: 124-channel recording, spatial deblurring and MRI integration methods. Electroencephalogr Clin Neurophysiol. 1994;90:337-358.
191. He B, Wang Y, Pak S, et al. Cortical source imaging from scalp electroencephalograms. Med Biol Eng Comput. 1996;34: 257-258.
192. Babiloni F, Babiloni C, Carducci F, et al. High resolution EEG: a new model-dependent spatial deblurring method using a realistically-shaped MR-constructed subject's head model. Electroencephalogr Clin Neurophysiol. 1997;102:69-80.
193. He B, Wang Y, Wu D. Estimating cortical potentials from scalp EEG's in a realistically shaped inhomogeneous head model by means of the boundary element method. IEEE Trans Biomed Eng. 1999;46:1264-1268.
194. He B, Lian J, Spencer KM, et al. A cortical potential imaging analysis of the P300 and novelty P3 components. Hum Brain Mapp. 2001;12:120-130.
195. He B, Zhang X, Lian J, et al. Boundary element method-based cortical potential imaging of somatosensory evoked potentials using subjects' magnetic resonance images. Neuroimage. 2002;16: 564-576.
196. Ollikainen JO, Vauhkonen M, Karjalainen PA, et al. A new computational approach for cortical imaging. IEEE Trans Med Imaging. 2001;20:325-332.
197. Towle VL, Cohen S, Alperin N, et al. Displaying electrocortico-graphic findings on gyral anatomy. Electroencephalogr Clin Neurophysiol. 1995;94:221-228.
198. He B, Liu Z. Multimodal functional neuroimaging: integrating functional MRI and EEG/MEG. IEEE Rev Biomed Eng. 2008:23-40.
199. Ahlfors SP, Simpson GV, Dale AM, et al. Spatiotemporal activity of a cortical network for processing visual motion revealed by MEG and fMRI. J Neurophysiol. 1999;82:2545-2555.
200. Fujimaki N, Hayakawa T, Nielsen M, et al. An fMRI-constrained MEG source analysis with procedures for dividing and grouping activation. Neuroimage. 2002;17:324-343.
201. Liu AK, Belliveau JW, Dale AM. Spatiotemporal imaging of human brain activity using functional MRI constrained magnetoencephalography data: Monte Carlo simulations. Proc Natl Acad Sci U S A. 1998;95:8945-8950.
202. Wagner M, Fuchs M, Kastner J. fMRI-constrained dipole fits and current density reconstructions. Proceedings of the 12th International Conference on Biomagnetism, Helsinki, 2000:785-788.
203. Babiloni F, Babiloni C, Carducci F, et al. Multimodal integration of high-resolution EEG and functional magnetic resonance imaging data: a simulation study. Neuroimage. 2003;19:1-15.
204. Babiloni F, Cincotti F, Babiloni C, et al. Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function. Neuroimage. 2005;24:118-131.
205. Phillips C, Mattout J, Rugg MD, et al. An empirical Bayesian solution to the source reconstruction problem in EEG. Neuroimage. 2005;24:997-1011.
206. Liu Z, Ding L, He B. Integration of EEG/MEG with MRI and fMRI. IEEE Eng Med Biol Mag. 2006;25:46-53.
207. Liu Z, He B. FMRI-EEG integrated cortical source imaging by use of time-variant spatial constraints. Neuroimage. 2008;39: 1198-1214.
208. Mattout J, Phillips C, Penny WD, et al. MEG source localization under multiple constraints: an extended Bayesian framework. Neuroimage. 2006;30:753-767.
209. Felleman DJ, Van Essen DC. Distributed hierarchical processing in the primate cerebral cortex. Cereb Cortex. 1991;1:1-47.
210. Laufs H, Holt JL, Elfont R, et al. Where the BOLD signal goes when alpha EEG leaves. Neuroimage. 2006;31:1408-1418.
211. Tyvaert L, Levan P, Grova C, et al. Effects of fluctuating physiological rhythms during prolonged EEG-fMRI studies. Clin Neurophysiol. 2008;119:2762-2774.
212. Laufs H, Kleinschmidt A, Beyerle A, et al. EEG-correlated fMRI of human alpha activity. Neuroimage. 2003;19:1463-1476.
213. Laufs H, Krakow K, Sterzer P, et al. Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest. Proc Natl Acad Sci U S A. 2003;100:11053-11058.
214. Laufs H, Hamandi K, Salek-Haddadi A, et al. Temporal lobe interictal epileptic discharges affect cerebral activity in "default mode" brain regions. Hum Brain Mapp. 2007;28:1023-1032.
215. Groening K, Brodbeck V, Moeller F, et al. Combination of EEG-fMRI and EEG source analysis improves interpretation of spike-associated activation networks in paediatric pharmacoresistant focal epilepsies. Neuroimage. 2009;46:827-833.
216. Vulliemoz S, Thornton R, Rodionov R, et al. The spatio-temporal mapping of epileptic networks: combination of EEG-fMRI and EEG source imaging. Neuroimage. 2009;46:834-843.
217. Brodbeck V, Lascano AM, Spinelli L, et al. Accuracy of EEG source imaging of epileptic spikes in patients with large brain lesions. Clin Neurophysiol. 2009;120:679-685.
218. Ioannides AA. Dynamic functional connectivity. Curr Opin Neurobiol. 2007;17:161-170.
219. McIntosh AR, Gonzalez-Lima F. Structural equation modeling and its application to network analysis in functional brain imaging. Hum Brain Mapp. 1994;2:2-22.
220. Arthurs OJ, Donovan T, Spiegelhalter DJ, et al. Intracortically distributed neurovascular coupling relationships within and between human somatosensory cortices. Cereb Cortex. 2007;17:661-668.
221. Otte A, Halsband U. Brain imaging tools in neurosciences. J Physiol Paris. 2006;99:281-292.
222. Adey WR, Walter DO, Hendrix CE. Computer techniques in correlation and spectral analyses of cerebral slow waves during discriminative behavior. Exp Neurol. 1961;3:501-524.
223. Gevins AS, Cutillo BA, Bressler SL, et al. Event-related covariances during a bimanual visuomotor task. II. Preparation and feedback. Electroencephalogr Clin Neurophysiol. 1989;74:147-160.
224. Lachaux JP, Rodriguez E, Martinerie J, et al. Measuring phase synchrony in brain signals. Hum Brain Mapp. 1999;8:194-208.
225. Urbano A, Babiloni C, Onorati P, et al. Dynamic functional coupling of high resolution EEG potentials related to unilateral internally triggered one-digit movements. Electroencephalogr Clin Neurophysiol. 1998;106:477-487.
226. Brovelli A, Ding M, Ledberg A, et al. Beta oscillations in a large-scale sensorimotor cortical network: directional influences revealed by Granger causality. Proc Natl Acad Sci U S A. 2004;101:9849-9854.
227. Strogatz SH. Exploring complex networks. Nature. 2001;410: 268-276.
228. Astolfi L, Cincotti F, Mattia D, et al. Estimation of the effective and functional human cortical connectivity with structural equation modeling and directed transfer function applied to high-resolution EEG. Magn Reson Imaging. 2004;22:1457-1470.
229. Astolfi L, Cincotti F, Babiloni C, et al. Estimation of the cortical connectivity by high-resolution EEG and structural equation modeling: simulations and application to finger tapping data. IEEE Trans Biomed Eng. 2005;52:757-768.
230. Wilke C, Ding L, He B. Estimation of time-varying connectivity patterns through the use of an adaptive directed transfer function. IEEE Trans Biomed Eng. 2008;55:2557-2564.
231. Wilke C, van Drongelen W, Kohrman M, et al. Identification of epileptogenic foci from causal analysis of ECoG interictal spike activity. Clin Neurophysiol. 2009;120:1449-1456.
232. Wilke C, van Drongelen W, Kohrman M, et al. Neocortical seizure foci localization by means of a directed transfer function method. Epilepsia. 2009;120:1449-1456.