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EEG/MEG Source Imaging: Methods, Challenges, and Open Issues

By Katrina Wendel, Outi Väisänen, Jaakko Malmivuo, Nevzat G. Gencer, Bart Vanrumste, Piotr Durka, Ratko Magjarević, Selma Supek, Mihail Lucian Pascu, Hugues Fontenelle and Rolando Grave de Peralta Menendez


We present the four key areas of research—preprocessing, the volume conductor, the forward problem, and the inverse problem—that affect the performance of EEG and MEG source imaging. In each key area we identify prominent approaches and methodologies that have open issues warranting further investigation within the community, challenges associated with certain techniques, and algorithms necessitating clarification of their implications. More than providing definitive answers we aim to identify important open issues in the quest of source localization

Topics: Review Article
Publisher: Hindawi Publishing Corporation
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Provided by: PubMed Central

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  1. (2004). 128-channel EEG source imaging in epilepsy: clinical yield and localization precision,”
  2. (2005). A computationally efficient method for accurately solving the EEG forward problem in a finely discretized head model,”
  3. (1998). A computer simulation study of cortical imaging from scalp potentials,”
  4. (1998). A critical analysis of linear inverse solutions to the neuroelectromagnetic inverse problem,”
  5. (2007). A glimpse into your vision,”
  6. (2006). a l ,A .I .D i a s ,a n dJ .P .V i e i r a ,“ A n a l y s i so f the EEG dynamics of epileptic activity in gelastic seizures using decomposition in independent components,”
  7. (1987). A Multigrid Tutorial,
  8. A.C.L.Barnard,I.M.Duck,andM.S.Lynn,“Theapplication of electromagnetic theory to electrocardiography—I: derivation of the integral equations,”
  9. (1993). A.M.DaleandM.I.Sereno,“Improvedlocalizationofcortical activity by combining EEG and MEG with MRI cortical surfacereconstruction:alinearapproach,”J o urnalo fC ogniti v e Neuroscience,
  10. (2000). Accuracy of two dipolar inverse algorithms applying reciprocity for forward calculation,”
  11. (2004). An advanced boundary element method (BEM) implementation for the forward problem of electromagnetic source imaging,”
  12. (1999). An evaluation of dipole reconstruction accuracy with spherical and realistic head models in
  13. (2000). B r i g g s ,V .E .H e n s o n ,a n dS .F .M c C o r m i c k ,A Multigrid Tutorial,
  14. (1990). Beyond topographic mapping: towards functionalanatomical imaging with 124-channel EEGs and 3-D MRIs,”
  15. (1989). Biscay,J.C.Jimenez,R.D.Pascual,andJ.Lemagne,“Projective methods for the magnetic direct problem,”
  16. (2000). C.E.DavilaandR.Srebro,“Subspaceaveragingofsteady-state visual evoked potentials,”
  17. (2005). Clinically Oriented Anatomy,
  18. (2006). Correlation between live and post mortem skull conductivity measurements,”
  19. Cramon, “Evoked dipole source potentials of the human auditory cortex,” Electroencephalography andClinicalNeurophysiology,vol.65,no.5,pp.344–360,1986.
  20. (1963). Determination of biological impedances,” in Physical Techniques in Biological Research,W .L .N a s t u k ,E d .
  21. (1983). Dielectric permittivity and electrical conductivity of fluid saturated bone,”
  22. (1984). Dielectric properties of fluid-saturated bone. The effect of variation in conductivity of immersion fluid,”
  23. (2000). Dipole location errors in electroencephalogram source analyssis due to volume conductor model errors,”
  24. (1995). EEG dipole localization bounds and MAP algorithms for head models with parameter uncertainties,”
  25. (1969). EEG electrode sensitivity—an application of reciprocity,”
  26. (1996). EEG localization accuracy improvements using realistically shaped head models,”
  27. (2006). Effect of measurement noise and electrode density on the spatial resolution of cortical potential distribution with different resistivity values for the skull,”
  28. (2004). Effect of skull resistivity on the spatial resolutions of
  29. (1999). Effects of local skull inhomogeneities on EEG source estimation,”MedicalEngineeringandPhysics,v ol.21,no .3,pp .
  30. (1999). Electrical conductivity imaging via contactless measurements,”
  31. (1992). Electrical Impedance Tomography Based on Current Density Imaging,
  32. (2004). Electrical neuroimaging based on biophysical constraints,”
  33. (2009). Electrophysiological correlates of affective blindsight,”
  34. (1998). Estimating the spatial Nyquist of the human
  35. (1996). Figures of merit to compare distributed linear inversesolutions,”BrainTopography,vol.9,no.2,pp.117–124,
  36. (2008). Hand movement direction decoded from
  37. (1997). High resolution EEG: a new model-dependent spatial deblurring method using a realistically-shaped MR-constructed subject’s head model,”
  38. (1969). High resolution frequency-wavenumber,”
  39. (2000). High-resolution electro-encephalogram: source estimates of Laplacian-transformed somatosensoryevoked potentials using a realistic subject head model constructed from magnetic resonance images,”
  40. (1993). How well does a three-sphere model predict positions of dipoles in a realistically shaped head?”
  41. (2003). In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head,”
  42. (2009). Incorporating anthropometric and craniometric data into realisticallyshaped volume conductor head models,”
  43. (1997). Influence of tissue resistivities on neuromagnetic fields and electric potentials studied with a finite element model of the head,”
  44. (1988). Interdependenceofinformationconveyedbythemagnetoencephalogram and the electroencephalogram,”
  45. (2004). Interpreting the BOLD signal,”
  46. (1992). Introduction to the Finite Element Method, Prentice-Hall,
  47. (2003). Iterative Methods for Sparse Linear Systems,S
  48. (2004). Keep it simple: a case for using classical minimum norm estimation in the analysis
  49. (1994). M.S.HamalainenandR.J.Ilmoniemi,“Interpretingmagnetic fields of the brain: minimum norm estimates,”
  50. (1999). Magnetic induction tomography. A measuring system for biological tissues,”
  51. (1993). Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain,”
  52. (1995). Mapping cognitive brain function with modern high-resolution electroencephalography,”
  53. (2002). Monte Carlo simulation studies of
  54. (1998). Multigridsolutionofthepotentialfieldinmodelingelectrical nerve stimulation,”
  55. (2001). n d e r e r ,G .K l o e s c h ,G .G r u b e r ,e ta l . ,“ L o w - r e s o l u t i o n brain electromagnetic tomography revealed simultaneously active frontal and parietal sleep spindle sources in the human cortex,”
  56. (1997). New finite difference formulations for general inhomogeneous anisotropic bioelectric problems,”
  57. (1995). Numerical Linear Algebra and Applications,
  58. (1995). Numerical Recipes in C,
  59. (1988). P i c t o n ,Handbook of Electroencephalography and Clinical Neurophysiology: Human Event-Related Potentials,E l s e v i e r ,
  60. (2001). Parametric modeling of somatosensory evoked potentials using discrete cosine transform,”
  61. (2002). Performance of an MEG adaptive-beamformer technique in the presence of correlated neural activities: effects on signal intensity and time-course estimates,”
  62. (2003). Phase synchronization of the ongoing
  63. (2005). Prediction of response speed by anticipatory high-frequency (gamma band) oscillations in the human brain,” Human Brain Mapping,v o l .2 4 ,n o .1 ,p p .
  64. (1989). Realistic conductivity geometry model of the human head for interpretation of neuromagnetic data,”
  65. (1991). Separation and identification of event-related potential components by brain electric source analysis,”ElectroencephalographyandClinicalNeurophysiology.
  66. (1993). Simulation studies of multiple dipole neuromagnetic source localization: model order and limits of source resolution,”
  67. (2001). Spatial enhancement of EEG data by surface Laplacian estimation: the use of magnetic resonance imagingbased head models,”
  68. (1996). Spatial sampling and filtering of EEG with spline laplacians to estimate cortical potentials,”
  69. (1997). Spatio-temporal modeling of neuromagnetic data—I: multi-source location versus
  70. (2008). t a s e v e n ,Z .A k a l i n - A c a r ,C .E .A c a r ,a n dN
  71. (1998). T h o m p s o n ,B .K .S o n i ,a n dN .P .W e a t h e r r i l l ,Handbook of Grid Generation,
  72. Taber’s Cyclopedic Medical Dictionary,F .A .D a v i s Company,
  73. (2000). The conductivity of the human skull: results of in vivo and in vitro measurements,”
  74. (1996). The dielectric properties of biological tissues—I: literature survey,”
  75. (2008). The influence of CSF on EEG sensitivity distributions of multilayered head models,”
  76. The nature of sources of bioelectric and biomagnetic fields,”
  77. (1999). The need for correct realistic geometry in the inverse EEG problem,”
  78. (1997). The resolution-field concept,”
  79. (1968). The resolving power of gross earth data,”
  80. (1967). The specific resistance of biological material—a compendium of data for the biomedical engineer and physiologist,”
  81. (2005). u r k a ,A .M a t y s i a k ,E .M .M o n t e s ,P .V .S o s a ,a n dK .J . Blinowska, “Multichannel matching pursuit and EEG inverse solutions,”
  82. (1987). uben, “Algebraic multigrid (AMG),”
  83. (2003). Uniqueness and reconstruction in magnetic resonance-electrical impedance tomography
  84. (1998). Volume conduction effects

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