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Volumn 117, Issue , 2015, Pages 439-448

A symmetric multivariate leakage correction for MEG connectomes

Author keywords

[No Author keywords available]

Indexed keywords

ALPHA RHYTHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BETA RHYTHM; BRAIN CORTEX; BRAIN FUNCTION; CONNECTOME; FRONTAL LOBE; HUMAN; IMAGE ANALYSIS; IMAGE RECONSTRUCTION; KERNEL METHOD; MAGNETOENCEPHALOGRAPHY; OSCILLATION; PRIORITY JOURNAL; RESTING STATE NETWORK; SIGNAL NOISE RATIO; TEMPORAL LOBE; COMPUTER SIMULATION; NERVE CELL NETWORK; PHYSIOLOGY; PROCEDURES; SIGNAL PROCESSING; STATISTICAL ANALYSIS;

EID: 84933060053     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2015.03.071     Document Type: Article
Times cited : (256)

References (46)
  • 1
    • 0035377249 scopus 로고    scopus 로고
    • Partial directed coherence: a new concept in neural structure determination
    • Baccala L.A., Sameshima K. Partial directed coherence: a new concept in neural structure determination. Biol. Cybern. 2001, 84(6):463-474.
    • (2001) Biol. Cybern. , vol.84 , Issue.6 , pp. 463-474
    • Baccala, L.A.1    Sameshima, K.2
  • 2
    • 84898730827 scopus 로고    scopus 로고
    • Fast transient networks in spontaneous human brain activity
    • Baker A.P., et al. Fast transient networks in spontaneous human brain activity. eLIFE 2014, 3:e01867.
    • (2014) eLIFE , vol.3 , pp. e01867
    • Baker, A.P.1
  • 3
    • 25444456446 scopus 로고    scopus 로고
    • Investigations into resting-state connectivity using independent component analysis
    • Beckmann C.F., et al. Investigations into resting-state connectivity using independent component analysis. Philos. Trans. R. Soc. B 2005, 360:1001-1013.
    • (2005) Philos. Trans. R. Soc. B , vol.360 , pp. 1001-1013
    • Beckmann, C.F.1
  • 4
    • 80053647086 scopus 로고    scopus 로고
    • Investigating the electrophysiological basis of resting state networks using magnetoencephalography
    • Brookes M.J., et al. Investigating the electrophysiological basis of resting state networks using magnetoencephalography. Proc. Natl. Acad. Sci. U. S. A. 2011, 108:16783-16788.
    • (2011) Proc. Natl. Acad. Sci. U. S. A. , vol.108 , pp. 16783-16788
    • Brookes, M.J.1
  • 5
    • 84866169453 scopus 로고    scopus 로고
    • Measuring functional connectivity in MEG: a multivariate approach insensitive to linear source leakage
    • Brookes M.J., et al. Measuring functional connectivity in MEG: a multivariate approach insensitive to linear source leakage. NeuroImage 2012, 63(2):910-920.
    • (2012) NeuroImage , vol.63 , Issue.2 , pp. 910-920
    • Brookes, M.J.1
  • 6
    • 84867039063 scopus 로고    scopus 로고
    • Task induced modulation of neural oscialtions in electrophysiological brain networks
    • Brookes M.J., et al. Task induced modulation of neural oscialtions in electrophysiological brain networks. NeuroImage 2012, 63(4):1918-1930.
    • (2012) NeuroImage , vol.63 , Issue.4 , pp. 1918-1930
    • Brookes, M.J.1
  • 7
    • 84894356246 scopus 로고    scopus 로고
    • Measuring temporal, spectral and spatial changes in electrophysiological brain network connectivity
    • Brookes M.J., et al. Measuring temporal, spectral and spatial changes in electrophysiological brain network connectivity. NeuroImage 2014, 91:282-299.
    • (2014) NeuroImage , vol.91 , pp. 282-299
    • Brookes, M.J.1
  • 9
    • 77950547730 scopus 로고    scopus 로고
    • Temporal dynamics of spontaneous MEG activity in brain networks
    • de Pasquale F., et al. Temporal dynamics of spontaneous MEG activity in brain networks. Proc. Natl. Acad. Sci. U. S. A. 2010, 107(13):6040-6045.
    • (2010) Proc. Natl. Acad. Sci. U. S. A. , vol.107 , Issue.13 , pp. 6040-6045
    • de Pasquale, F.1
  • 10
    • 84885193306 scopus 로고    scopus 로고
    • Utility of partial correlation for characterising brain dynamics: MVPA-based assessment of regularisation and network selection
    • (PRNI 2013)
    • Duff E., et al. Utility of partial correlation for characterising brain dynamics: MVPA-based assessment of regularisation and network selection. Proceedings- 2013 3rd International Workshop on Pattern Recognition in Neuroimaging 2013, 58-61. (PRNI 2013).
    • (2013) Proceedings- 2013 3rd International Workshop on Pattern Recognition in Neuroimaging , pp. 58-61
    • Duff, E.1
  • 11
    • 84883053367 scopus 로고    scopus 로고
    • Intracranial EEG evaluation of relationship within a resting state network
    • Duncan D., et al. Intracranial EEG evaluation of relationship within a resting state network. Clin. Neurophysiol. 2013, 124(10):1943-1951.
    • (2013) Clin. Neurophysiol. , vol.124 , Issue.10 , pp. 1943-1951
    • Duncan, D.1
  • 13
    • 45849134070 scopus 로고    scopus 로고
    • Sparse inverse covariance estimation with the graphical lasso
    • Friedman J., et al. Sparse inverse covariance estimation with the graphical lasso. Biostatistics 2008, 9(3):432-441.
    • (2008) Biostatistics , vol.9 , Issue.3 , pp. 432-441
    • Friedman, J.1
  • 14
    • 0041924877 scopus 로고    scopus 로고
    • Dynamic causal modelling
    • Friston K.J., et al. Dynamic causal modelling. NeuroImage 2003, 19:1273-1302.
    • (2003) NeuroImage , vol.19 , pp. 1273-1302
    • Friston, K.J.1
  • 15
    • 0035895222 scopus 로고    scopus 로고
    • Dynamic imaging of coherent sources: studying neural interactions in the human brain
    • Gross J., et al. Dynamic imaging of coherent sources: studying neural interactions in the human brain. Proc. Natl. Acad. Sci. U. S. A. 2001, 98:694-699.
    • (2001) Proc. Natl. Acad. Sci. U. S. A. , vol.98 , pp. 694-699
    • Gross, J.1
  • 16
    • 84855883044 scopus 로고    scopus 로고
    • Frequency-dependent functional connectivity within resting-state networks: an atlas-basedMEG beamformer solution
    • Hillebrand A., et al. Frequency-dependent functional connectivity within resting-state networks: an atlas-basedMEG beamformer solution. NeuroImage 2012, 59:3909-3921.
    • (2012) NeuroImage , vol.59 , pp. 3909-3921
    • Hillebrand, A.1
  • 17
    • 84861574104 scopus 로고    scopus 로고
    • Large-scale cortical correlation structure of spontaneous oscillatory activity
    • Hipp J.F., et al. Large-scale cortical correlation structure of spontaneous oscillatory activity. Nat. Neurosci. 2012, 15(6):884-890.
    • (2012) Nat. Neurosci. , vol.15 , Issue.6 , pp. 884-890
    • Hipp, J.F.1
  • 18
    • 0032957150 scopus 로고    scopus 로고
    • A sensor-weightedoverlapping-sphere head model and exhaustive head model comparison for MEG
    • Huang M.X., et al. A sensor-weightedoverlapping-sphere head model and exhaustive head model comparison for MEG. Phys. Med. Biol. 1999, 44(2):423-440.
    • (1999) Phys. Med. Biol. , vol.44 , Issue.2 , pp. 423-440
    • Huang, M.X.1
  • 19
    • 0032629347 scopus 로고    scopus 로고
    • Fast and robust fixed-point algorithms for independent component analysis
    • Hyvärinen A. Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans. Neural Netw. 1999, 10(3):626-634.
    • (1999) IEEE Trans. Neural Netw. , vol.10 , Issue.3 , pp. 626-634
    • Hyvärinen, A.1
  • 20
    • 84862979110 scopus 로고    scopus 로고
    • FSL
    • Jenkinson M., et al. FSL. NeuroImage 2012, 62:782-790.
    • (2012) NeuroImage , vol.62 , pp. 782-790
    • Jenkinson, M.1
  • 21
    • 84902240499 scopus 로고    scopus 로고
    • Directed transfer function is not influenced by volume conduction-inexpedient pre-processing should be avoided
    • Kaminski M., Blinowska K.J. Directed transfer function is not influenced by volume conduction-inexpedient pre-processing should be avoided. Front. Comput. Neurosci. 2014, 8:61.
    • (2014) Front. Comput. Neurosci. , vol.8 , pp. 61
    • Kaminski, M.1    Blinowska, K.J.2
  • 22
    • 16444378435 scopus 로고
    • On the nonorthogonality problem connected with the use of atomic wave functions in the theory of molecules and crystals
    • Löwdin P.-O. On the nonorthogonality problem connected with the use of atomic wave functions in the theory of molecules and crystals. J. Chem. Phys. 1950, 18:365-375.
    • (1950) J. Chem. Phys. , vol.18 , pp. 365-375
    • Löwdin, P.-O.1
  • 23
    • 84861762655 scopus 로고    scopus 로고
    • Inferring task-related networks using independent component analysis in magnetoencephalography
    • Luckhoo H., et al. Inferring task-related networks using independent component analysis in magnetoencephalography. NeuroImage 2012, 62:530-541.
    • (2012) NeuroImage , vol.62 , pp. 530-541
    • Luckhoo, H.1
  • 24
    • 84899963052 scopus 로고    scopus 로고
    • Graph theoretical analysis of resting-stateMEG data: identifying interhemispheric connectivity and the default mode
    • Maldjian J.A., et al. Graph theoretical analysis of resting-stateMEG data: identifying interhemispheric connectivity and the default mode. NeuroImage 2014, 96:88-94.
    • (2014) NeuroImage , vol.96 , pp. 88-94
    • Maldjian, J.A.1
  • 25
    • 85006219828 scopus 로고    scopus 로고
    • A signal-processing pipeline for magnetoencephalography resting-state networks
    • Mantini D., et al. A signal-processing pipeline for magnetoencephalography resting-state networks. Brain Connect. 2011, 1(1):49-59.
    • (2011) Brain Connect. , vol.1 , Issue.1 , pp. 49-59
    • Mantini, D.1
  • 26
    • 33748653805 scopus 로고    scopus 로고
    • Partial correlation for functional brain interactivity investigation in functional MRI
    • Marrelec G., et al. Partial correlation for functional brain interactivity investigation in functional MRI. NeuroImage 2006, 32(228-237).
    • (2006) NeuroImage , vol.32 , Issue.228-237
    • Marrelec, G.1
  • 27
    • 84878118796 scopus 로고    scopus 로고
    • Frequency specific interactions of MEG resting state activity within and across brain networks as revealed by the multivariate interaction measure
    • Marzetti L., et al. Frequency specific interactions of MEG resting state activity within and across brain networks as revealed by the multivariate interaction measure. NeuroImage 2013, 79:172-183.
    • (2013) NeuroImage , vol.79 , pp. 172-183
    • Marzetti, L.1
  • 28
    • 84859447804 scopus 로고    scopus 로고
    • Exact covariance thresholding into connected components for large-scale graphical lasso
    • Mazumder R., Hastie T. Exact covariance thresholding into connected components for large-scale graphical lasso. J. Mach. Learn. Res. 2012, 13:723-726.
    • (2012) J. Mach. Learn. Res. , vol.13 , pp. 723-726
    • Mazumder, R.1    Hastie, T.2
  • 29
    • 84875395423 scopus 로고    scopus 로고
    • The graphical lasso: new insights and alternatives
    • Mazumder R., Hastie T. The graphical lasso: new insights and alternatives. Electron. J. Stat. 2012, 6:2125-2149.
    • (2012) Electron. J. Stat. , vol.6 , pp. 2125-2149
    • Mazumder, R.1    Hastie, T.2
  • 30
    • 84867056427 scopus 로고    scopus 로고
    • The University of Newcastle Identification Toolbox (UNIT)
    • Ninness B., et al. The University of Newcastle Identification Toolbox (UNIT). IFAC World Congress 2005, 1-6.
    • (2005) IFAC World Congress , pp. 1-6
    • Ninness, B.1
  • 31
    • 4444355027 scopus 로고    scopus 로고
    • Identifying true brain interaction from EEG using the imaginary part of coherency
    • Nolte G., et al. Identifying true brain interaction from EEG using the imaginary part of coherency. J. Clin. Neurophysiol. 2004, 115:2292-2307.
    • (2004) J. Clin. Neurophysiol. , vol.115 , pp. 2292-2307
    • Nolte, G.1
  • 32
    • 79551668253 scopus 로고    scopus 로고
    • FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data
    • Oostenveld R., et al. FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput. Intell. Neurosci. 2011, 2011:156869.
    • (2011) Comput. Intell. Neurosci. , vol.2011 , pp. 156869
    • Oostenveld, R.1
  • 33
    • 84859107675 scopus 로고    scopus 로고
    • Discovering oscillatory interaction networks with M/EEG: challenges and breakthroughs
    • Palva S., Palva J.M. Discovering oscillatory interaction networks with M/EEG: challenges and breakthroughs. Trends Cogn. Sci. 2012, 16(4):219-230.
    • (2012) Trends Cogn. Sci. , vol.16 , Issue.4 , pp. 219-230
    • Palva, S.1    Palva, J.M.2
  • 34
    • 0002475292 scopus 로고    scopus 로고
    • Functional neuroimaging by synthetic aperture magnetometry (SAM)
    • Tohoku Univ. Press, Sendai, Japan, T. Yoshimoto, M. Kotani, S. Kuriki, H. Karibe, N. Nakasato (Eds.)
    • Robinson S.E., Vrba J. Functional neuroimaging by synthetic aperture magnetometry (SAM). Recent Advances in Biomagnetism 1999, 302-305. Tohoku Univ. Press, Sendai, Japan. T. Yoshimoto, M. Kotani, S. Kuriki, H. Karibe, N. Nakasato (Eds.).
    • (1999) Recent Advances in Biomagnetism , pp. 302-305
    • Robinson, S.E.1    Vrba, J.2
  • 35
    • 0023158840 scopus 로고
    • Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem
    • Sarvas J. Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem. Phys. Med. Biol. 1987, 32(1):11-22.
    • (1987) Phys. Med. Biol. , vol.32 , Issue.1 , pp. 11-22
    • Sarvas, J.1
  • 36
    • 84862999728 scopus 로고    scopus 로고
    • The future of FMRI connectivity
    • Smith S.M. The future of FMRI connectivity. NeuroImage 2012, 62:1257-1266.
    • (2012) NeuroImage , vol.62 , pp. 1257-1266
    • Smith, S.M.1
  • 37
    • 78649717035 scopus 로고    scopus 로고
    • Network modelling methods for FMRI
    • Smith S.M., et al. Network modelling methods for FMRI. NeuroImage 2011, 54:875-891.
    • (2011) NeuroImage , vol.54 , pp. 875-891
    • Smith, S.M.1
  • 38
    • 84861459104 scopus 로고    scopus 로고
    • The organization of physiological brain networks
    • Stam C.J., van Straaten E.C.W. The organization of physiological brain networks. Clin. Neurophysiol. 2012, 123:1067-1087.
    • (2012) Clin. Neurophysiol. , vol.123 , pp. 1067-1087
    • Stam, C.J.1    van Straaten, E.C.W.2
  • 39
    • 34249997316 scopus 로고    scopus 로고
    • Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources
    • Stam C.J., et al. Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources. Hum. Brain Mapp. 2007, 28(11):1178-1193.
    • (2007) Hum. Brain Mapp. , vol.28 , Issue.11 , pp. 1178-1193
    • Stam, C.J.1
  • 40
    • 84880326067 scopus 로고    scopus 로고
    • The WU-Minn Human Connetome Project: an overview
    • Van Essen D.C., et al. The WU-Minn Human Connetome Project: an overview. NeuroImage 2013, 80:62-97.
    • (2013) NeuroImage , vol.80 , pp. 62-97
    • Van Essen, D.C.1
  • 41
    • 84984552597 scopus 로고    scopus 로고
    • Localization of brain electrical activity via linearly constrained minimum variance spatial filtering
    • Van Veen B.D., et al. Localization of brain electrical activity via linearly constrained minimum variance spatial filtering. IEEE Trans. Biomed. Eng. 1997, 44:867-880.
    • (1997) IEEE Trans. Biomed. Eng. , vol.44 , pp. 867-880
    • Van Veen, B.D.1
  • 42
    • 84880327399 scopus 로고    scopus 로고
    • Learning and comparing functional connectomes across subjects
    • Varoquaux G., Craddock R.C. Learning and comparing functional connectomes across subjects. NeuroImage 2013, 80:405-415.
    • (2013) NeuroImage , vol.80 , pp. 405-415
    • Varoquaux, G.1    Craddock, R.C.2
  • 44
    • 84904051956 scopus 로고    scopus 로고
    • About the electrophysiological basis of resting state networks
    • Wens V., et al. About the electrophysiological basis of resting state networks. Clin. Neurophysiol. 2014, 125:1711-1713.
    • (2014) Clin. Neurophysiol. , vol.125 , pp. 1711-1713
    • Wens, V.1
  • 45
    • 84880330489 scopus 로고    scopus 로고
    • Biophysical network models and the human connectome
    • Woolrich M.W., Stephan K.E. Biophysical network models and the human connectome. NeuroImage 2013, 80:330-338.
    • (2013) NeuroImage , vol.80 , pp. 330-338
    • Woolrich, M.W.1    Stephan, K.E.2
  • 46
    • 79960280623 scopus 로고    scopus 로고
    • MEG beamforming using Bayesian PCA for adaptive data covariance matrix regularization
    • Woolrich M.W., et al. MEG beamforming using Bayesian PCA for adaptive data covariance matrix regularization. NeuroImage 2011, 57:1466-1479.
    • (2011) NeuroImage , vol.57 , pp. 1466-1479
    • Woolrich, M.W.1


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