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10 - Integration of electrical neuroimaging with other functional imaging methods

Published online by Cambridge University Press:  15 December 2009

Christoph M. Michel
Affiliation:
Université de Genève
Thomas Koenig
Affiliation:
University Hospital of Psychiatry, Berne, Switzerland
Daniel Brandeis
Affiliation:
Department of Child and Adolescent Psychiatry, University of Zurich, Switzerland and Central Institute of Mental Health, Mannheim, Grmany
Lorena R. R. Gianotti
Affiliation:
Universität Zürich
Jiří Wackermann
Affiliation:
Institute for Frontier Areas of Psychology and Mental Health, Freiburg im Breisgau, Germany
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Summary

Introduction

Integrating evidence from different imaging modalities is important to overcome specific limitations of any given imaging method, such as insensitivity of the EEG to unsynchronized neural events, or the lack of fMRI sensitivity to events of low metabolic demand. Processes that are visible in one modality may be related in a nontrivial way to other processes visible in another modality and insight may only be obtained by integrating both methods through a common analysis. For example, brain activity at rest seems to be at least partly determined by an interaction of cortical rhythms (visible to EEG but not to fMRI) with sub-cortical activity (visible to fMRI, but usually not to EEG without averaging). A combination of EEG and fMRI data during rest may thus be more informative than the sum of two separate analyses in both modalities.

Integration is also an important source of converging evidence about specific aspects and general principles of neural functions and their dysfunctions in certain pathologies. This is because not only electrical, but also energetic, biochemical, hemodynamic and metabolic processes characterize neural states and functions, and because brain structure provides crucial constraints upon neural functions. Focusing on multimodal integration of functional data should not distract from the privileged status of the electric field as the primary direct, noninvasive real-time measure of neural transmission.

The preceding chapters illustrate how electrical neuroimaging has turned scalp EEG into an imaging modality which directly captures the full temporal dynamics of neural activity in the brain.

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Publisher: Cambridge University Press
Print publication year: 2009

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References

Horwitz, B, Poeppel, D. How can EEG/MEG and fMRI/PET data be combined? Human Brain Mapping 2002;17:1–3.CrossRefGoogle ScholarPubMed
Laufs, H, Daunizeau, J, Carmichael, DW, Kleinschmidt, A. Recent advances in recording electrophysiological data simultaneously with magnetic resonance imaging. Neuroimage 2008;40:515–528.CrossRefGoogle ScholarPubMed
Vitacco, D, Brandeis, D, Pascual-Marqui, RD, Martin, E. Correspondence of event-related potential tomography and functional magnetic resonance imaging during language processing. Human Brain Mapping 2002;17:4–12.CrossRefGoogle ScholarPubMed
Babiloni, F, Carducci, F, Cincotti, Fet al. Linear inverse source estimate of combined EEG and MEG data related to voluntary movements. Human Brain Mapping 2001;14:197–209.CrossRefGoogle ScholarPubMed
Trujillo-Barreto, NJ, Martínez-Montes, E, Melie-García, L, Valdés-Sosa, PA. A symmetrical Bayesian model for fMRI and EEG/MEG neuroimage fusion. International Journal of Bioelectromagnetism (online journal). 2001;3.Google Scholar
Wagner, M, Fuchs, M. Integration of functional MRI, structural MRI, EEG, and MEG. International Journal of Bioelectromagnetism (online journal). 2001;3.Google Scholar
Debener, S, Ullsperger, M, Siegel, M, Engel, AK. Single-trial EEG-fMRI reveals the dynamics of cognitive function. Trends in Cognitive Sciences 2006;10:558–563.CrossRefGoogle ScholarPubMed
Debener, S, Ullsperger, M, Siegel, Met al. Trial-by-trial coupling of concurrent electroencephalogram and functional magnetic resonance imaging identifies the dynamics of performance monitoring. Journal of Neuroscience 2005;25:11730–11737.CrossRefGoogle ScholarPubMed
Goldman, RI, Stern, JM, EngelJ, Jr. J, Jr., Cohen, MS. Simultaneous EEG and fMRI of the alpha rhythm. Neuroreport 2002;13:2487–2492.CrossRefGoogle ScholarPubMed
Jann, K, Wiest, R, Hauf, Met al. BOLD correlates of continuously fluctuating epileptic activity isolated by independent component analysis. Neuroimage 2008; 42:635–648.CrossRefGoogle ScholarPubMed
Martinez-Montes, E, Valdes-Sosa, PA, Miwakeichi, F, Goldman, RI, Cohen, MS. Concurrent EEG/fMRI analysis by multiway Partial Least Squares. Neuroimage 2004;22:1023–1034.CrossRefGoogle ScholarPubMed
Cohen, D. Magnetoencephalography: detection of the brain's electrical activity with a superconducting magnetometer. Science 1972;175:664–666.CrossRefGoogle ScholarPubMed
Hamalainen, MS, Hari, R, Ilmoniemi, RJ, Knuutila, JE, Lounasmaa, OV. Magnetoencephalography-theory, instrumentation, and applications to noninvasive studies of the working human brain. Review of Modern Physics 1993;65:413–497.CrossRefGoogle Scholar
Hari, R, Levanen, S, Raij, T. Timing of human cortical functions during cognition: role of MEG. Trends in Cognitive Sciences 2000;4:455–462.CrossRefGoogle ScholarPubMed
Berger, H. Über das Elektroenkephalogramm des Menschen. Archiv für Psychiatrie und Nervenkrankheiten 1929;87:527–570.CrossRefGoogle Scholar
Lehmann, D, Kavanagh, RH, Fender, DH. Field studies of averaged visually evoked EEG potentials in a patient with a split chiasm. Electroencephalography and Clinical Neurophysiology 1969;26:193–199.CrossRefGoogle Scholar
Riera, JJ, Valdes, PA, Tanabe, K, Kawashima, R. A theoretical formulation of the electrophysiological inverse problem on the sphere. Physics in Medicine and Biology 2006;51:1737–1758.CrossRefGoogle ScholarPubMed
Cohen, D, Cuffin, BN. Demonstration of useful differences between magnetoencephalogram and electroencephalogram. Electroencephalography and Clinical Neurophysiology 1983;56:38–51.CrossRefGoogle ScholarPubMed
Malmivuo, JA, Suihko, VE. Effect of skull resistivity on the spatial resolutions of EEG and MEG. IEEE Transactions on Biomedical Engineering 2004;51:1276–1280.CrossRefGoogle ScholarPubMed
Ramantani, G, Boor, R, Paetau, Ret al. MEG versus EEG: influence of background activity on interictal spike detection. Journal of Clinical Neurophysiology 2006;23:498–508.CrossRefGoogle ScholarPubMed
Jongh, A, Munck, JC, Goncalves, SI, Ossenblok, P. Differences in MEG/EEG epileptic spike yields explained by regional differences in signal-to-noise ratios. Journal of Clinical Neurophysiology 2005;22:153–158.CrossRefGoogle ScholarPubMed
Fuchs, M, Wagner, M, Wischmann, HAet al. Improving source reconstructions by combining bioelectric and biomagnetic data. Electroencephalography and Clinical Neurophysiology 1998;107:93–111.CrossRefGoogle ScholarPubMed
Sharon, D, Hamalainen, MS, Tootell, RBH, Halgren, E, Belliveau, JW. The advantage of combining MEG and EEG: comparison to fMRI in focally stimulated visual cortex. Neuroimage 2007;36:1225–1235.CrossRefGoogle ScholarPubMed
Goncalves, S, Munck, JC, Verbunt, JP, Heethaar, RM, da Silva, FH. In vivo measurement of the brain and skull resistivities using an EIT-based method and the combined analysis of SEF/SEP data. IEEE Transactions on Biomedical Engineering 2003;50:1124–1128.CrossRefGoogle ScholarPubMed
Hopf, JM, Luck, SJ, Boelmans, Ket al. The neural site of attention matches the spatial scale of perception. Journal of Neuroscience 2006;26:3532–3540.CrossRefGoogle Scholar
Bast, T, Ramantani, G, Boppel, Tet al. Source analysis of interictal spikes in polymicrogyria: loss of relevant cortical fissures requires simultaneous EEG to avoid MEG misinterpretation. Neuroimage 2005;25:1232–1241.CrossRefGoogle ScholarPubMed
Lauritzen, M. Relationship of spikes, synaptic activity, and local changes of cerebral blood flow. Journal of Cerebral Blood Flow & Metabolism 2001;21:1367–1383.CrossRefGoogle ScholarPubMed
Logothetis, NK, Pauls, J, Augath, M, Trinath, T, Oeltermann, A. Neurophysiological investigation of the basis of the fMRI signal. Nature 2001;412:150–157.CrossRefGoogle ScholarPubMed
Burke, M, Buhrle, C. BOLD response during uncoupling of neuronal activity and CBF. Neuroimage 2006;32:1–8.CrossRefGoogle ScholarPubMed
Singh, M, Kim, S, Kim, TS. Correlation between BOLD-fMRI and EEG signal changes in response to visual stimulus frequency in humans. Magnetic Resonance in Medicine 2003;49:108–114.CrossRefGoogle ScholarPubMed
Janz, C, Heinrich, SP, Kornmayer, J, Bach, M, Hennig, J. Coupling of neural activity and BOLD fMRI response: new insights by combination of fMRI and VEP experiments in transition from single events to continuous stimulation. Magnetic Resonance in Medicine 2001;46:482–486.CrossRefGoogle ScholarPubMed
Wan, X, Riera, J, Iwata, K, Takahashi, M, Wakabayashi, T, Kawashima, R. The neural basis of the hemodynamic response nonlinearity in human primary visual cortex: implications for neurovascular coupling mechanism. Neuroimage 2006;32:616–625.CrossRefGoogle ScholarPubMed
Mulert, C, Jager, L, Propp, Set al. Sound level dependence of the primary auditory cortex: simultaneous measurement with 61-channel EEG and fMRI. Neuroimage 2005;28:49–58.CrossRefGoogle ScholarPubMed
Arthurs, OJ, Williams, EJ, Carpenter, TA, Pickard, JD, Boniface, SJ. Linear coupling between functional magnetic resonance imaging and evoked potential amplitude in human somatosensory cortex. Neuroscience 2000;101:803–806.CrossRefGoogle ScholarPubMed
Horovitz, SG, Rossion, B, Skudlarski, P, Gore, JC. Parametric design and correlational analyses help integrating fMRI and electrophysiological data during face processing. Neuroimage 2004;22:1587–1595.CrossRefGoogle ScholarPubMed
Meltzer, JA, Negishi, M, Mayes, LC, Constable, RT. Individual differences in EEG theta and alpha dynamics during working memory correlate with fMRI responses across subjects. Clinical Neurophysiology 2007;118:2419–2436.CrossRefGoogle ScholarPubMed
Vanni, S, Warnking, J, Dojat, Met al. Sequence of pattern onset responses in the human visual areas: an fMRI constrained VEP source analysis. Neuroimage 2004;21:801–817.CrossRefGoogle ScholarPubMed
Di Russo, F, Martinez, A, Sereno, MI, Pitzalis, S, Hillyard, SA. Cortical sources of the early components of the visual evoked potential. Human Brain Mapping 2002;15:95–111.CrossRefGoogle ScholarPubMed
Liu, Z, He, B. FMRI-EEG integrated cortical source imaging by use of time-variant spatial constraints. Neuroimage 2008;39:1198–1214.CrossRefGoogle ScholarPubMed
Hopf, J-M, Boehler, CN, Luck, SJet al. Direct neurophysiological evidence for spatial suppression surrounding the focus of attention in vision. Proceedings of the National Academy of Sciences, USA 2006;103:1053–1058.CrossRefGoogle ScholarPubMed
Martinez, A, Anllo-Vento, L, Sereno, MIet al. Involvement of striate and extrastriate visual cortical areas in spatial attention. Nature Neuroscience 1999;2:364–369.CrossRefGoogle ScholarPubMed
Morand, S, Thut, G, Peralta, RGet al. Electrophysiological evidence for fast visual processing through the human koniocellular pathway when stimuli move. Cerebral Cortex 2000;10:817–825.CrossRefGoogle ScholarPubMed
Steger, J, Imhof, K, Denoth, Jet al. Brain mapping of bilateral visual interactions in children. Psychophysiology 2001;38:243–253.CrossRefGoogle ScholarPubMed
Mulert, C, Jager, L, Schmitt, Ret al. Integration of fMRI and simultaneous EEG: towards a comprehensive understanding of localization and time-course of brain activity in target detection. Neuroimage 2004;22:83–94.CrossRefGoogle ScholarPubMed
Brem, S, Bucher, K, Halder, Pet al. Evidence for developmental changes in the visual word processing network beyond adolescence. Neuroimage 2006;29:822–837.CrossRefGoogle ScholarPubMed
Bucher, K, Dietrich, T, Marcar, VLet al. Maturation of luminance- and motion-defined form perception beyond adolescence: a combined ERP and fMRI study. Neuroimage 2006;31:1625–1636.CrossRefGoogle ScholarPubMed
Halder, P, Brem, S, Bucher, Ket al. Electrophysiological and hemodynamic evidence for late maturation of hand force control under visual feedback. Human Brain Mapping 2007;28:69–84.CrossRefGoogle ScholarPubMed
Schulz, E, Maurer, U, Mark, Set al. Impaired semantic processing during sentence reading in children with dyslexia: combined fMRI and ERP evidence. Neuroimage 2008;41:153–168.CrossRefGoogle ScholarPubMed
Richter, W, Richter, M. The shape of the fMRI BOLD response in children and adults changes systematically with age. Neuroimage 2003;20:1122–1131.CrossRefGoogle ScholarPubMed
Brauer, J, Neumann, J, Friederici, AD. Temporal dynamics of perisylvian activation during language processing in children and adults. Neuroimage 2008; 41:1484–1492.CrossRefGoogle ScholarPubMed
Lemieux, L, Allen, PJ, Franconi, F, Symms, MR, Fish, . Recording of EEG during fMRI experiments: patient safety. Magnetic Resonance in Medicine 1997;38:943–952.CrossRefGoogle ScholarPubMed
Lemieux, L, Krakow, K, Fish, DR. Comparison of spike-triggered functional MRI BOLD activation and EEG dipole model localization. Neuroimage 2001;14:1097–1104.CrossRefGoogle ScholarPubMed
Lazeyras, F, Zimine, I, Blanke, O, Perrig, SH, Seeck, M. Functional MRI with simultaneous EEG recording: feasibility and application to motor and visual activation. Journal of Magnetic Resonance Imaging 2001;13:943–948.CrossRefGoogle ScholarPubMed
Vasios, CE, Angelone, LM, Purdon, PLet al. EEG/(f)MRI measurements at 7 Tesla using a new EEG cap (“InkCap”). Neuroimage 2006;33:1082–1092.CrossRefGoogle Scholar
Mullinger, K, Brookes, M, Stevenson, C, Morgan, P, Bowtell, R. Exploring the feasibility of simultaneous electroencephalography/functional magnetic resonance imaging at 7 T. Magnetic Resonance Imaging 2008; 26:968–977.CrossRefGoogle ScholarPubMed
Mandelkow, H, Halder, P, Boesiger, P, Brandeis, D. Synchronization facilitates removal of MRI artefacts from concurrent EEG recordings and increases usable bandwidth. Neuroimage 2006;32:1120–1126.CrossRefGoogle ScholarPubMed
Debener, S, Mullinger, KJ, Niazy, RK, Bowtell, RW. Properties of the ballistocardiogram artefact as revealed by EEG recordings at 1. 5, 3 and 7 T static magnetic field strength. International Journal of Psychophysiology 2008;67:189–199.CrossRefGoogle Scholar
Allen, PJ, Josephs, O, Turner, R. A method for removing imaging artifact from continuous EEG recorded during functional MRI. Neuroimage 2000;12:230–239.CrossRefGoogle ScholarPubMed
Allen, PJ, Polizzi, G, Krakow, K, Fish, DR, Lemieux, L. Identification of EEG events in the MR scanner: the problem of pulse artifact and a method for its subtraction. Neuroimage 1998;8:229–239.CrossRefGoogle Scholar
Gotman, J, Benar, C-G, Dubeau, F. Combining EEG and fMRI in epilepsy: a multimodal tool for epilepsy research. Journal of Magnetic Resonance Imaging 2006;23:906–920.CrossRefGoogle ScholarPubMed
Laufs, H, Duncan, JS. Electroencephalography/functional MRI in human epilepsy: what it currently can and cannot do. Current Opinion in Neurology 2007;20:417–423.CrossRefGoogle Scholar
Mandelkow, H, Halder, P, Brandeis, Det al. Heart beats Brain: The problem of detecting alpha waves by neuronal current imaging in joint EEG-MRI experiments. Neuroimage 2007;37:149–163.CrossRefGoogle ScholarPubMed
Brookes, MJ, Mullinger, KJ, Stevenson, CM, Morris, PG, Bowtell, R. Simultaneous EEG source localisation and artifact rejection during concurrent fMRI by means of spatial filtering. Neuroimage 2008;40:1090–1104.CrossRefGoogle ScholarPubMed
Seeck, M, Lazeyras, F, Michel, CMet al. Non invasive epileptic focus localization using EEG-triggered functional MRI and electromagnetic tomography. Electroencephalography and Clinical Neurophysiology 1998;106:508–512.CrossRefGoogle ScholarPubMed
Krakow, K, Woermann, FG, Symms, MRet al. EEG-triggered functional MRI of interictal epileptiform activity in patients with partial seizures. Brain 1999;122:1679–1688.CrossRefGoogle ScholarPubMed
Lazeyras, F, Blanke, O, Perrig, Set al. EEG-triggered functional MRI in patients with pharmacoresistant epilepsy. Journal of Magnetic Resonance Imaging 2000;12:177–185.3.0.CO;2-3>CrossRefGoogle ScholarPubMed
Lemieux, L. Electroencephalographycorrelated functional MR imaging studies of epileptic activity. Neuroimaging Clinics of North America 2004;14:487–506.CrossRefGoogle ScholarPubMed
Al-Asmi, A, Benar, CG, Gross, DWet al. fMRI activation in continuous and spike-triggered EEG-fMRI studies of epileptic spikes. Epilepsia 2003;44:1328–1339.CrossRefGoogle ScholarPubMed
Gotman, J, Grova, C, Bagshaw, Aet al. Generalized epileptic discharges show thalamocortical activation and suspension of the default state of the brain. Proceedings of the National Academy of Sciences USA 2005;102:15236–15240.CrossRefGoogle Scholar
Aghakhani, Y, Bagshaw, AP, Benar, CGet al. fMRI activation during spike and wave discharges in idiopathic generalized epilepsy. Brain 2004;127:1127–1144.CrossRefGoogle ScholarPubMed
Laufs, H, Lengler, U, Hamandi, K, Kleinschmidt, A, Krakow, K. Linking generalized spike-and-wave discharges and resting state brain activity by using EEG/fMRI in a patient with absence seizures. Epilepsia 2006;47:444–448.CrossRefGoogle Scholar
Hawco, CS, Bagshaw, AP, Lu, Y, Dubeau, F, Gotman, J. BOLD changes occur prior to epileptic spikes seen on scalp EEG. Neuroimage 2007;35:1450–1458.CrossRefGoogle ScholarPubMed
Moeller, F, Siebner, HR, Wolff, Set al. Changes in activity of striato-thalamocortical network precede generalized spike wave discharges. Neuroimage 2008;9:1839–1849.CrossRefGoogle Scholar
Gotman, J.Epileptic networks studied with EEG-fMRI. Epilepsia 2008;49:42–51.CrossRefGoogle ScholarPubMed
Salek-Haddadi, A, Diehl, B, Hamandi, Ket al. Hemodynamic correlates of epileptiform discharges: an EEG-fMRI study of 63 patients with focal epilepsyBrain Res 2006;1088:148–166.CrossRefGoogle ScholarPubMed
Lantz, G, Spinelli, L, Menendez, RG, Seeck, M, Michel, CM. Localization of distributed sources and comparison with functional MRI. Epileptic Disorders 2001;Special Issue:45–58.Google ScholarPubMed
Alarcon, G, Guy, CN, Binnie, CDet al. Intracerebral propagation of interictal activity in partial epilepsy: implications for source localisation. Journal of Neurology, Neurosurgery and Psychiatry 1994;57:435–449.CrossRefGoogle ScholarPubMed
Lantz, G, Spinelli, L, Seeck, Met al. Propagation of interictal epileptiform activity can lead to erroneous source localizations: A 128 channel EEG mapping study. Journal of Clinical Neurophysiology 2003;20:311–319.CrossRefGoogle ScholarPubMed
Boor, R, Jacobs, J, Hinzmann, Aet al. Combined spike-related functional MRI and multiple source analysis in the non-invasive spike localization of benign rolandic epilepsy. Clinical Neurophysiology 2007;118:901–909.CrossRefGoogle ScholarPubMed
Bagshaw, AP, Kobayashi, E, Dubeau, F, Pike, GB, Gotman, J. Correspondence between EEG-fMRI and EEG dipole localisation of interictal discharges in focal epilepsy. Neuroimage 2006;30:417–425.CrossRefGoogle ScholarPubMed
Grova, C, Daunizeau, J, Kobayashi, Eet al. Concordance between distributed EEG source localization and simultaneous EEG-fMRI studies of epileptic spikes. Neuroimage 2008;39:755–774.CrossRefGoogle ScholarPubMed
Grouiller, F, Vercueil, L, Krainik, Aet al. A comparative study of different artefact removal algorithms for EEG signals acquired during functional MRI. Neuroimage 2007;38:124–137.CrossRefGoogle ScholarPubMed
Vulliemoz, S, Thornton, R, Rodionov, Ret al. The spatio-temporal mapping of epileptic networks: combination of EEG-fMRI and EEG source imaging. Neuroimage 2009; in press.CrossRefGoogle ScholarPubMed
Groening, K, Brodbeck, V, Moeller, Fet al. Combination of EEG-fMRI and EEG source analysis improves interpretation of spike-associated activation networks in paediatric pharmacoresistant focal epilepsies. Neuroimage 2009; in press.CrossRefGoogle ScholarPubMed
Sadato, N, Nakamura, S, Oohashi, Tet al. Neural networks for generation and suppression of alpha rhythm: a PET study. Neuroreport 1998;9:893–897.CrossRefGoogle ScholarPubMed
Buchsbaum, MS, Kessler, R, King, A, Johnson, J, Cappelletti, J. Simultaneous cerebral glucography with positron emission tomography and topographic electroencephalography. Progress in Brain Research 1984;62:263–269.CrossRefGoogle ScholarPubMed
Dierks, T, Jelic, V, Pascual-Marqui, RDet al. Spatial pattern of cerebral glucose metabolism (PET) correlates with localization of intracerebral EEG-generators in Alzheimer's disease. Clinical Neurophysiology 2000;111:1817–1824.CrossRefGoogle ScholarPubMed
Feige, B, Scheffler, K, Esposito, Fet al. Cortical and subcortical correlates of electroencephalographic alpha rhythm modulation. Journal of Neurophysiology 2005;93:2864–2872.CrossRefGoogle ScholarPubMed
Moosmann, M, Ritter, P, Krastel, Iet al. Correlates of alpha rhythm in functional magnetic resonance imaging and near infrared spectroscopy. Neuroimage 2003;20:145–158.CrossRefGoogle ScholarPubMed
Jong, R, Coles, MGH, Logan, GD, Gratton, G. In search of the point of no return: the control of response processes. Journal of Experimental Psychology: Human Perception and Performance 1990;16:164–182.Google ScholarPubMed
Mantini, D, Perrucci, MG, Del Gratta, C, Romani, GL, Corbetta, M. Electrophysiological signatures of resting state networks in the human brain. Proceedings of the National Academy of Sciences, USA 2007;104:13170–13175.CrossRefGoogle ScholarPubMed
Laufs, H, Holt, JL, Elfont, Ret al. Where the BOLD signal goes when alpha EEG leaves. Neuroimage 2006;31:1408–1418.CrossRefGoogle ScholarPubMed
Laufs, H, Kleinschmidt, A, Beyerle, Aet al. EEG-correlated fMRI of human alpha activity. Neuroimage 2003;19:1463–1467.CrossRefGoogle ScholarPubMed
Laufs, H, Krakow, K, Sterzer, Pet al. Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest. Proceedings of the National Academy of Sciences, USA 2003;100:11053–11058.CrossRefGoogle ScholarPubMed
Scheeringa, R, Bastiaansen, MCM, Petersson, KMet al. Frontal theta EEG activity correlates negatively with the default mode network in resting state. International Journal of Psychophysiology 2008;67:242–251.CrossRefGoogle ScholarPubMed
Bénar, C-G, Schön, D, Grimault, Set al. Single-trial analysis of oddball event-related potentials in simultaneous EEG-fMRI. Human Brain Mapping 2007;28:602–613.CrossRefGoogle ScholarPubMed
Konn, D, Gowland, P, Bowtell, R. MRI detection of weak magnetic fields due to an extended current dipole in a conducting sphere: a model for direct detection of neuronal currents in the brain. Magnetic Resonance in Medicine 2003;50:40–49.CrossRefGoogle Scholar
Blagoev, KB, Mihaila, B, Travis, BJet al. Modelling the magnetic signature of neuronal tissue. Neuroimage 2007;37:137–148.CrossRefGoogle ScholarPubMed
Murakami, S, Okada, Y. Contributions of principal neocortical neurons to magnetoencephalography and electroencephalography signals. Journal of Physiology 2006;575:925–936.CrossRefGoogle ScholarPubMed
Lee, L, Harrison, LM, Mechelli, A. A report of the functional connectivity workshop, Dusseldorf 2002. Neuroimage 2003;19:457–465.CrossRefGoogle ScholarPubMed
Massimini, M, Ferrarelli, F, Huber, Ret al. Breakdown of cortical effective connectivity during sleep. Science 2005;309:2228–2232.CrossRefGoogle ScholarPubMed
Komssi, S, Kähkönen, S. The novelty value of the combined use of electroencephalography and transcranial magnetic stimulation for neuroscience research. Brain Research Reviews 2006;52:183–192.CrossRefGoogle ScholarPubMed
Kähkönen, S, Wilenius, J. Effects of alcohol on TMS-evoked N100 responses. Journal of Neuroscience Methods 2007;166:104–108.CrossRefGoogle ScholarPubMed
Kähkönen, S, Wilenius, J, Nikulin, VV, Ollikainen, M, Ilmoniemi, RJ. Alcohol reduces prefrontal cortical excitability in humans: a combined TMS and EEG study. Neuropsychopharmacology 2003;28:747–754.CrossRefGoogle ScholarPubMed
Romei, V, Brodbeck, V, Michel, Cet al. Spontaneous fluctuations in posterior {α}-band EEG activity reflect variability in excitability of human visual areas. Cerebral Cortex 2007;18:2010–2018.CrossRefGoogle ScholarPubMed
Fuchs, M, Kastner, J, Wagner, M, Hawes, S, Ebersole, JS. A standardized boundary element method volume conductor model. Clinical Neurophysiology 2002;113:702–712.CrossRefGoogle ScholarPubMed
Park, HJ, Kwon, JS, Youn, Tet al. Statistical parametric mapping of LORETA using high density EEG and individual MRI: application to mismatch negativities in schizophrenia. Human Brain Mapping 2002;17:168–178.CrossRefGoogle Scholar
Spinelli, L, Andino, SG, Lantz, G, Seeck, M, Michel, CM. Electromagnetic inverse solutions in anatomically constrained spherical head models. Brain Topography 2000;13:115–125.CrossRefGoogle ScholarPubMed
Cardenas, VA, Chao, LL, Blumenfeld, Ret al. Using automated morphometry to detect associations between ERP latency and structural brain MRI in normal adults. Human Brain Mapping 2005;25:317–327.CrossRefGoogle ScholarPubMed
Stufflebeam, SM, Witzel, T, Mikulski, Set al. A non-invasive method to relate the timing of neural activity to white matter microstructural integrity. Neuroimage 2008;42:710–716.CrossRefGoogle ScholarPubMed

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