5 EEG Source Imaging and Multimodal Neuroimaging
121
25. B. Fischl, D.H. Salat, E. Busa et al., Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33(3), 341–355 (2002)
26. J.M. Ford, B.J. Roach, V.A. Palzes, D.H. Mathalon, Using concurrent EEG and fMRI to probe
the state of the brain in schizophrenia. NeuroImage-Clin. 12, 429–441 (2016)
27. K. Friston, L. Harrison, J. Daunizeau et al., Multiple sparse priors for the M/EEG inverse
problem. Neuroimage 39(3), 1104–1120 (2008)
28. K. Friston, C. Chu, J. Mourão-Miranda et al., Bayesian decoding of brain images. Neuroimage
39(1), 181–205 (2008)
29. K.J. Friston, W. Penny, C. Phillips et al., Classical and Bayesian inference in neuroimaging:
theory. Neuroimage 16(2), 465–483 (2002)
30. M. Fuchs, M. Wagner, J. Kastner, Boundary element method volume conductor models for
EEG source reconstruction. Clin. Neurophysiol. 112(8), 1400–1407 (2001)
31. L. Geddes, L. Baker, The specific resistance of biological material—a compendium of data for
the biomedical engineer and physiologist. Med. Biol. Eng. 5(3), 271–293 (1967)
32. G.H. Golub, M. Heath, G. Wahba, Generalized cross-validation as a method for choosing a
good ridge parameter. Technometrics 21(2), 215–223 (1979)
33. S.I. Gonçalves, J.C. de Munck, J.P. Verbunt et al., In vivo measurement of the brain and skull
resistivities using an EIT-based method and realistic models for the head. IEEE Trans. Biomed.
Eng. 50(6), 754–767 (2003)
34. R.L. Goris, T. Putzeys, J. Wagemans, F.A. Wichmann, A neural population model for visual
pattern detection. Psychol. Rev. 120(3), 472 (2013)
35. R. Grech, T. Cassar, J. Muscat et al., Review on solving the inverse problem in EEG source
analysis. J. NeuroEng. Rehabil. 5(1), 25 (2008)
36. D. Gutiérrez, A. Nehorai, C.H. Muravchik, Estimating brain conductivities and dipole source
signals with EEG arrays. IEEE Trans. Biomed. Eng. 51(12), 2113–2122 (2004)
37. M. Hämäläinen, R. Hari, R.J. Ilmoniemi et al., Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain. Rev. Mod. Phys.
65(2), 413 (1993)
38. H. Hallez, B. Vanrumste, R. Grech et al., Review on solving the forward problem in EEG
source analysis. J. NeuroEng. Rehabil. 4(1), 46 (2007)
39. M.S. Hamalainen, Interpreting Measured Magnetic Fields of the Brain: Estimates of Current
Distributions (Helsinki University of Technology, Rep, 1984)
40. Hansen PC (1999) The L-curve and its use in the numerical treatment of inverse problems
41. O. Hauk, D.G. Wakeman, R. Henson, Comparison of noise-normalized minimum norm estimates for MEG analysis using multiple resolution metrics. Neuroimage 54(3), 1966–1974
(2011)
42. R.J. Huster, S. Debener, T. Eichele, C.S. Herrmann, Methods for simultaneous EEG-fMRI: an
introductory review. J. Neurosci. 32(18), 6053–6060 (2012)
43. B.H. Jansen, V.G. Rit, Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns. Biol. Cybern. 73(4), 357–366 (1995)
44. J. Jorge, W. Van der Zwaag, P. Figueiredo, EEG–fMRI integration for the study of human brain
function. Neuroimage 102, 24–34 (2014)
45. Y. Lai, W. Van Drongelen, L. Ding et al., Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra-and intra-cranial electrical potential recordings. Clin.
Neurophysiol. 116(2), 456–465 (2005)
46. X. Lei, C. Qiu, P. Xu, D. Yao, A parallel framework for simultaneous EEG/fMRI analysis:
methodology and simulation. Neuroimage 52(3), 1123–1134 (2010)
47. X. Lei, D. Ostwald, J. Hu et al., Multimodal functional network connectivity: an EEG-fMRI
fusion in network space. PLoS ONE 6(9), e24642 (2011)
48. R. Li, T. Potter, W. Huang, Y. Zhang, Enhancing performance of a hybrid EEG-fNIRS system
using channel selection and early temporal features. Front. Hum. Neurosci. 11, 462 (2017)
49. A.K. Liu, J.W. Belliveau, A.M. Dale, Spatiotemporal imaging of human brain activity using
functional MRI constrained magnetoencephalography data: Monte Carlo simulations. Proc.
Natl. Acad. Sci. 95(15), 8945–8950 (1998)
121
25. B. Fischl, D.H. Salat, E. Busa et al., Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33(3), 341–355 (2002)
26. J.M. Ford, B.J. Roach, V.A. Palzes, D.H. Mathalon, Using concurrent EEG and fMRI to probe
the state of the brain in schizophrenia. NeuroImage-Clin. 12, 429–441 (2016)
27. K. Friston, L. Harrison, J. Daunizeau et al., Multiple sparse priors for the M/EEG inverse
problem. Neuroimage 39(3), 1104–1120 (2008)
28. K. Friston, C. Chu, J. Mourão-Miranda et al., Bayesian decoding of brain images. Neuroimage
39(1), 181–205 (2008)
29. K.J. Friston, W. Penny, C. Phillips et al., Classical and Bayesian inference in neuroimaging:
theory. Neuroimage 16(2), 465–483 (2002)
30. M. Fuchs, M. Wagner, J. Kastner, Boundary element method volume conductor models for
EEG source reconstruction. Clin. Neurophysiol. 112(8), 1400–1407 (2001)
31. L. Geddes, L. Baker, The specific resistance of biological material—a compendium of data for
the biomedical engineer and physiologist. Med. Biol. Eng. 5(3), 271–293 (1967)
32. G.H. Golub, M. Heath, G. Wahba, Generalized cross-validation as a method for choosing a
good ridge parameter. Technometrics 21(2), 215–223 (1979)
33. S.I. Gonçalves, J.C. de Munck, J.P. Verbunt et al., In vivo measurement of the brain and skull
resistivities using an EIT-based method and realistic models for the head. IEEE Trans. Biomed.
Eng. 50(6), 754–767 (2003)
34. R.L. Goris, T. Putzeys, J. Wagemans, F.A. Wichmann, A neural population model for visual
pattern detection. Psychol. Rev. 120(3), 472 (2013)
35. R. Grech, T. Cassar, J. Muscat et al., Review on solving the inverse problem in EEG source
analysis. J. NeuroEng. Rehabil. 5(1), 25 (2008)
36. D. Gutiérrez, A. Nehorai, C.H. Muravchik, Estimating brain conductivities and dipole source
signals with EEG arrays. IEEE Trans. Biomed. Eng. 51(12), 2113–2122 (2004)
37. M. Hämäläinen, R. Hari, R.J. Ilmoniemi et al., Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain. Rev. Mod. Phys.
65(2), 413 (1993)
38. H. Hallez, B. Vanrumste, R. Grech et al., Review on solving the forward problem in EEG
source analysis. J. NeuroEng. Rehabil. 4(1), 46 (2007)
39. M.S. Hamalainen, Interpreting Measured Magnetic Fields of the Brain: Estimates of Current
Distributions (Helsinki University of Technology, Rep, 1984)
40. Hansen PC (1999) The L-curve and its use in the numerical treatment of inverse problems
41. O. Hauk, D.G. Wakeman, R. Henson, Comparison of noise-normalized minimum norm estimates for MEG analysis using multiple resolution metrics. Neuroimage 54(3), 1966–1974
(2011)
42. R.J. Huster, S. Debener, T. Eichele, C.S. Herrmann, Methods for simultaneous EEG-fMRI: an
introductory review. J. Neurosci. 32(18), 6053–6060 (2012)
43. B.H. Jansen, V.G. Rit, Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns. Biol. Cybern. 73(4), 357–366 (1995)
44. J. Jorge, W. Van der Zwaag, P. Figueiredo, EEG–fMRI integration for the study of human brain
function. Neuroimage 102, 24–34 (2014)
45. Y. Lai, W. Van Drongelen, L. Ding et al., Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra-and intra-cranial electrical potential recordings. Clin.
Neurophysiol. 116(2), 456–465 (2005)
46. X. Lei, C. Qiu, P. Xu, D. Yao, A parallel framework for simultaneous EEG/fMRI analysis:
methodology and simulation. Neuroimage 52(3), 1123–1134 (2010)
47. X. Lei, D. Ostwald, J. Hu et al., Multimodal functional network connectivity: an EEG-fMRI
fusion in network space. PLoS ONE 6(9), e24642 (2011)
48. R. Li, T. Potter, W. Huang, Y. Zhang, Enhancing performance of a hybrid EEG-fNIRS system
using channel selection and early temporal features. Front. Hum. Neurosci. 11, 462 (2017)
49. A.K. Liu, J.W. Belliveau, A.M. Dale, Spatiotemporal imaging of human brain activity using
functional MRI constrained magnetoencephalography data: Monte Carlo simulations. Proc.
Natl. Acad. Sci. 95(15), 8945–8950 (1998)