Skip to main content
SpringerLink
Log in

Multimodal Imaging from Neuroelectromagnetic and Functional Magnetic Resonance Recordings

  • Chapter
Modeling and Imaging of Bioelectrical Activity

Part of the book series: Bioelectric Engineering ((BEEG))

Abstract

Human neocortical processes involve temporal and spatial scales spanning several orders of magnitude, from the rapidly shifting somatosensory processes characterized by a temporal scale of milliseconds and a spatial scales of few square millimeters to the memory processes, involving time periods of seconds and spatial scale of square centimeters. Information about the brain activity can be obtained by measuring different physical variables arising from the brain processes, such as the increase in consumption of oxygen by the neural tissues or a variation of the electric potential over the scalp surface. All these variables are connected in direct or indirect way to the neural ongoing processes, and each variable has its own spatial and temporal resolution. The different neuroimaging techniques are then confined to the spatiotemporal resolution offered by the monitored variables. For instance, it is known from physiology that the temporal resolution of the hemodynamic deoxyhemoglobin increase/decrease lies in the range of 1–2 seconds, while its spatial resolution is generally observable with the current imaging techniques at few mm scale. Today, no neuroimaging method allows a spatial resolution on a mm scale and a temporal resolution on a msec scale. Hence, it is of interest to study the possibility to integrate the information offered by the different physiological variables in a unique mathematical context. This operation is called the “multimodal integration” of variable X and Y, when the X variable has typically particular appealing spatial resolution property (mm scale) and the Y variable has particular attractive temporal properties (on a ms scale). Nevertheless, the issue of several temporal and spatial domains is critical in the study of the brain functions, since different properties could become observable, depending on the spatio-temporal scales at which the brain processes are measured.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Ahlfors, S.P., Simpson, G.V., Dale, A.M., Belliveau J.W., Liu, A.K., Korvenoja, A., Virtanen, J., Huotilainen, M., Tootell, R.B., Aronen, H.J., and Ilmoniemi, R.J., 1999, Spatiotemporal activity of a cortical network for processing visual motion revealed by MEG and fMRI, Journal of Neurophysiology, 82(5):2545–55.

    Google Scholar 

  • Allison, T., McCarthy, G., Wood, C.C., Darcey, T.M., Spencer, D.D., and Williamson, P.D., 1989, Human cortical potentials evoked by stimulation of the median nerve. I. Cytoarchitectonic areas generating short-latency activity, Journal of Neurophysiology 62(3):694–710.

    Google Scholar 

  • Allison, T., McCarthy, G., Luby, M., Puce, A., and Spencer, D.D., 1996, Localization of functional regions of human mesial cortex by somatosensory evoked potential recording and by cortical stimulation, Electroencephalography & Clinical Neurophysiology 100(2):126–40.

    Article  Google Scholar 

  • Arieli, A., Sterkin, A., Grinvald, A., Aertsen, A.D., 1996, Dynamics of ongoing activity: Explanation of the large variability in evoked cortical responses, Science 273:1868–71.

    Article  Google Scholar 

  • Babiloni, F., Babiloni, C., Carducci, F., Fattorini L. et al., 1997, A high resolution EEG: a new model-dependent spatial deblurring method using a realistically shaped MR-constructed subjects head model, Electroenceph. clin. Neurophysiol. 102: 69–80.

    Article  Google Scholar 

  • Babiloni, F., Carducci, F., Cincotti, F., Del Gratta, C., Roberti, G.M., Romani, G.L., Rossini, P.M., and Babiloni, C., 2000, Integration of High Resolution EEG and Functional Magnetic Resonance in the Study of Human Movement-Related Potentials, Methods of Information in Medicine 39(2):179–82.

    Google Scholar 

  • Babiloni, F., Carducci, F., Cincotti, F., Del Gratta, C., Pizzella, V, Romani, G.L., Rossini, P.M., Tecchio F., and Babiloni, C., 2001, Linear inverse source estimate of combined EEG and MEG data related to voluntary movements, Human Brain Mapping, 14(4):197–210.

    Article  Google Scholar 

  • Baillet, S. and Garnero, L., 1997, A bayesian framework to introducing anatomo-functional priors in the EEG/MEG inverse problem, IEEE Trans. Biom. Eng. 44:374–85.

    Article  Google Scholar 

  • Baillet, S., Garnero, L., Marin, G., and Hugonin, P., 1999, J Combined MEG and EEG source imaging by minimization of mutual information, IEEE Trans. Biom. Eng. 46:522–34.

    Article  Google Scholar 

  • Baillet, S., Leahy, R., Singh, M., Shattuck D., and Mosher, J., 2001, Supplementary Motor Area Activation Preceding Voluntary Finger Movements as Evidenced by Magnetoencephalography and fMRI, International Journal of Bioelectromagnetism, 1(3).

    Google Scholar 

  • Bandettini, P. A. (1993) Functional MRI of the Brain, Soc. Magnetic Resonance in Medicine, Berkeley, CA.

    Google Scholar 

  • Blamire, A. M., Ogawa, S., Ugurbil, K., Rothman, D., McCarthy, G., Ellerman, J. M., Hyder, F., Rattner, Z., and Shulman, R. G., 1992, Proc. Natl. Acad. Sci. USA 89:11069–73.

    Article  Google Scholar 

  • Braitemberg, V. and Schuz, A., 1991. Anatomy of the cortex. Statistics and Geometry. New York: Springer-Verlag.

    Google Scholar 

  • Belliveau J. W. 1993. MRI techniques for functional mapping of the human brain: integration with PET, EEG/MEG and infrared spectroscopy. In: Quantification of Brain Function. Elsevier Science Publishers (Excerpta Medica), Amsterdam. 639–67.

    Google Scholar 

  • Beisteiner, R., Erdler, M., Teichtmeister, C., Diemling, M., Moser, E., Edward, V., and Deecke L., 1997, Magnetoencephalography may help to improve functional MRI brain mapping, European Journal of Neuroscience 9(5):1072–7.

    Article  Google Scholar 

  • Bonmassar, G., Van Der Moortele, P., Purdon, P., Jaaskelainen, I., Ives, J., Vaughan, T., Ugurbil K., and Belliveau J., 2001, 7 Tesla interleaved EEG and fMRI recordings: BOLD measurements, Neurolmage 13(6):S6.

    Article  Google Scholar 

  • Cohen, D., Cuffin B., Yunokuchi, K., Manieski, R., Purcell, C., Cosgrove, G.R., Ives, J., Kennedy, J., and Schomer D., 1990, MEG versus EEG localization test using implanted sources in the human brain, Ann. Neurol., 28:811–817.

    Article  Google Scholar 

  • Dale, A.M., and Sereno, M., 1993, Improved localization of cortical activity by combining EEG anf MEG with MRI cortical surface reconstruction: a linear approach, J. Cognitive Neuroscience, 5:162–76.

    Article  Google Scholar 

  • Dale, A. M., Fischl, B., Sereno, M. I., 1999, Cortical surface-based analysis. I. Segmentation and surface reconstruction, Neuroimage 9(2):179–94.

    Article  Google Scholar 

  • Dale, A., Liu, A., Fischl, B., Buckner, R., Belliveau, J. W., Lewine, J., and Halgren, E., 2000, Dynamic Statistical Parametric Mapping: Combining fMRI and MEG for High-Resolution Imaging of Cortical Activity, Neuron 26:55–67.

    Article  Google Scholar 

  • Ebersole, J. Defining epileptogenic foci: past, present, future., 1997, Journal of Clinical Neurophysiology 14:470–483.

    Article  Google Scholar 

  • Ebersole, J., 1999, The last word, Journal of Clinical Neurophysiology 16:297–302.

    Article  Google Scholar 

  • Edlinger, G., Wach, P., and Pfurtscheller, G., 1998, On the realization of an analytic high-resolution EEG, IEEE Trans. Biomed. Eng. 45:736–45.

    Article  Google Scholar 

  • Fuchs, M., Wischmann, H.A., Wagner, M., and Krüger, J., 1995, Coordinate System Matching for Neuromagnetic and Morphological Reconstruction Overlay, IEEE Transactions on Biomedical Engineering. 42:416–420.

    Article  Google Scholar 

  • Fuchs M., Wagner M., Wischmann H.A., Kohler T., Theissen A., Drenckhahn R., Buchner H., 1998, Improving source reconstruction by combining bioelectrical and biomagnetic data. Electroenceph clin Neurophysiol 107:69–80.

    Article  Google Scholar 

  • George J. S., Aine, C. J., Mosher, J. C., Schmidt D. M., Ranken D. M., Schlitt H. A., Wood, C. C., Lewine J. D., Sanders, J. A., and Belliveau, J. W., 1995, Mapping function in the human brain with MEG, anatomical MRI and functional MRI. J. Clin. Neurophysiol. 12:406–431.

    Article  Google Scholar 

  • Gevins, A., 1989, Dynamic functional topography of cognitive task, Brain Topogr., 2:37–56.

    Article  Google Scholar 

  • Gevins, A., Brickett, P., Reutter, B., and Desmond, J., 1991, Seeing through the skull: advanced EEGs use MRIs to accurately measure cortical activity from the scalp, Brain Topogr. 4:125–131.

    Article  Google Scholar 

  • Gevins, A., Le, J., Leong, H., McEvoy, L.K., Smith, M.E., 1999, Deblurring, J Clin Neurophysiol, 16(3):204–13.

    Article  Google Scholar 

  • Gevins, A., Le, J., Martin, N., Brickett, P., Desmond, J., and Reutter, B., 1994, High resolution EEG: 124-channel recording, spatial deblurring and MRI integration methods, Electroenceph. clin. Neurophysiol. 39:337–358.

    Article  Google Scholar 

  • Grave de Peralta Menendez, R., Gonzalez Andino S., and Lutkenhoner B., 1996, Figures of merit to compare linear distributed inverse solutions, Brain Topograph 9(2):117–24.

    Article  Google Scholar 

  • Grave de Peralta, R., Hauk, O., Gonzalez Andino, S., Vogt, H., and Michel, C.M., 1997, Linear inverse solution with optimal resolution kernels applied to the electromagnetic tomography, Human Brain Mapping 5, 454–67.

    Article  Google Scholar 

  • Grave de Peralta Menendez, R., and Gonzalez Andino S.L., 1998, Distributed source models: standard solutions and new developments. In: Uhl, C. (ed): Analysis of neurophysiological brain functioning. Springer Verlag, pp. 176–201.

    Google Scholar 

  • Grinvald, A., Lieke, E., Frostig, R.D., Gilbert, C.D., and Wiesel, T.N., 1986, Functional architecture of cortex revealed by optical imaging of intrinsic signals, Nature 324(6095):361–4.

    Article  Google Scholar 

  • Hämäläinen, M., and Ilmoniemi, R., 1984, Interpreting measured magnetic field of the brain: Estimates of the current distributions. Technical report TKK-F-A559, Helsinki Univesity of Technology.

    Google Scholar 

  • He, B., Wang, Y., Pak, S., and Ling, Y., 1996, Cortical source imaging from scalp electroencephalograms, Med. & Biol. Eng. & Comput., 34 Suppl, part 2, 257–8.

    Article  Google Scholar 

  • He, B., 1999, Brain Electrical Source Imaging: Scalp Laplacian mapping and cortical imaging, Critical Reviews in Biomedical Engineering, 27, 149–188.

    Google Scholar 

  • He B., Wang Y., Wu D., 1999, 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 46:1264–8.

    Article  Google Scholar 

  • He, B., Lian, J., Li, G., 2001, High-resolution EEG: a new realistic geometry spline Laplacian estimation technique, Clinical Neurophysiology 112(5):845–52.

    Article  Google Scholar 

  • He, B., Zhang, Lian, J., Sasaki, H., Wu, D., Towle, V.L. 2002. Boundary Element Method Based Cortical Potential Imaging of Somatosensory Evoked Potentials Using Subjects’ Magnetic Resonance Images, Neuroimage, in press.

    Google Scholar 

  • Heinze H.J., Mangun, G.R., Burchert, W., Hinrichs, H., Scholz, M., Munte, T.F., Gos, A., Scherg, M., Johannes, S., and Hundeshagen, H., 1994, Combined spatial and temporal imaging of brain activity during visual selective attention in humans, Nature 372:543–46.

    Article  Google Scholar 

  • Heinze H.J., Hinrichs H., Scholz M., Burchert W., and Mangun G.R., 1998, Neural mechanisms of global and local processing. A combined PET and ERP study. J. Cogn. Neurosci. 10:485–98.

    Article  Google Scholar 

  • Huang-Hellinger F.R., Breiter H.C., McCormak G., Cohen M.S., Kwong K.K., Sutton J.P., Savoy R.L., Weisskoff R.M., Davis T.L., Baker J.R., Belliveau J.W., and Rosen B.R. 1995. Simultaneous functional magnetic resonance imaging and electrophysiological recording. Hum. Brain Map. 3:13–23.

    Article  Google Scholar 

  • Ives, J.R., Warach, S., Schmitt, F., Edelman, R.R., and Schomer, D.L., 1993, Monitoring the patient’s EEG during echo-planar MRI, Electroenceph. clin. Neurophysiol. 87:417–420.

    Article  Google Scholar 

  • Kampe, K.K., Jones, R.A., and Auer, D.P., 2000, Frequency dependence of the functional MRI response after electrical median nerve stimulation, Human Brain Mapping, 9(2):106–14

    Article  Google Scholar 

  • Kim, S., Ashe, J., Hendrich, K., Ellermann, J., Merkle, H., Ugurbil, K., and Georgopulos, A. 1993, Functional magnetic resonance imaging of motor cortex: hemispheric asymmetry and handedness, Science 261: 615–7.

    Article  Google Scholar 

  • Kim, D.S., Duong T.Q., Kim S.G., 2000, High-resolution mapping of iso-orientation columns by fMRI, Nature Neuroscience 3(2):164–9.

    Article  Google Scholar 

  • Krakow, K., Woermann, F.G., Symms, M.R., Allen, P.J., Barker, G.J., Duncan, J.S., and Fish, D.R., 1999, EEG-triggered functional MRI of intertictal epileptiform activity in patients with partial seizures, Brain 122:1679–88.

    Article  Google Scholar 

  • Korvenoja, A., Huttunen, J., Salli, E., Pohjonen, H., Martinkauppi, S., Palva, J.M., Lauronen, L., Virtanen, J., Ilmoniemi, R.J., and Aronen, H.J., 1999, Activation of multiple cortical areas in response to somatosensory stimulation: combined magnetoencephalographic and functional magnetic resonance imaging, Human Brain Mapping, 8(1):13–27.

    Article  Google Scholar 

  • Lamusuo, S., Forss, N., Ruottinen, H.M., Bergman, J., Makela, J.P., Mervaala, E., Solin, O., Rinne, J.K., Ruotsalainen, U., Ylinen, A., Vapalahti, M., Hari, R., and Rinne, J.O., 1999, [18F]FDG-PET and whole-scalp MEG localization of epileptogenic cortex, Epilepsia 40:921–30.

    Article  Google Scholar 

  • Lawson, C.L., and Hanson, R., J. 1974, Solving least squares problems. Prentice Hall, Englewood Cliff, New Jersey.

    MATH  Google Scholar 

  • Le, J., and Gevins, A., 1993, A method to reduce blur distortion from EEG’s using a realistic head model. IEEE Trans. Biomed. Eng. 40:517–528.

    Article  Google Scholar 

  • Lemieux, L., Krakow, K., Fish, D.R., 2001, Comparison of spike-triggered functional MRI BOLD activation and EEG dipole model localization, Neuroimage, 14(5):1097–104.

    Article  Google Scholar 

  • Liu, A.K., Belliveau, J.W., and Dale, A.M., 1998, Spatiotemporal imaging of human brain activity using functional MRI constrained magnetoencephalography data: Monte Carlo simulations, Proc. Nat. Acad. Sc., 95(15):8945–50.

    Article  Google Scholar 

  • Liu, A.K., 2000, Spatiotemporal brain imaging, PhD dissertation, Massachusetts Institute of Technology, Cambridge, MA.

    Google Scholar 

  • Logothetis N.K., Pauls J., Augath M., Trinath T., Oeltermann A., 2001, Neurophysiological investigation of the basis of the fMRI signal. Nature. 412(6843):150–7.

    Article  Google Scholar 

  • Luck S.J. 1999. Direct and indirect integration of event-related potentials, functional magnetic resonance images, and single-unit recordings, Hum. Brain Map. 8:115–201.

    Article  Google Scholar 

  • Magistretti, P.J., Pellerin, L., Rothman, D.L., and Shulman, R.G., 1999, Energy on demand, Science 283(5401):496–7.

    Article  Google Scholar 

  • Malonek D., Grinvald A., 1996, Interactions between electrical activity and cortical microcirculation revealed by imaging spectroscopy: implications for functional brain mapping. Science, 272(5261):551–4.

    Article  Google Scholar 

  • Menke W: Geophysical Data Analysis: Discrete Inverse Theory. San Diego, CA Academic Press, 1989.

    MATH  Google Scholar 

  • Menon, V., Ford, J.M., Lim, K.O., Glover, G.H., and Pfefferbaum, A., 1997, Combined Event-Related fMRI and EEG Evidence For Temporal-Parietal Cortex Activation During Target Detection, NeuroReport 8: 3029–37.

    Article  Google Scholar 

  • Morioka, T., Mizushima, A., Yamamoto, T., Tobimatsu, S., Matsumoto, S., Hasuo, K., Fujii, K., and Fukui, M., 1995, Functional mapping of the sensorimotor cortex: combined use of magnetoencephalography, functional MRI, and motor evoked potentials, Neuroradiology 37:526–30.

    Article  Google Scholar 

  • Nunez, P.L., Silberstein, R., 2000, On the relationship of synaptic activity to macroscopic measurements: does co-registration of EEG with fMRI make sense? Brain Topogr. 13(2):79–96.

    Article  Google Scholar 

  • Nunez, P. Electric fields of the brain. Oxford University Press, New York, 1981.

    Google Scholar 

  • Nunez, P. L., 1995, Neocortical dynamics and human EEG rhythms, Oxford University Press, New York.

    Google Scholar 

  • Opitz, B., Mecklinger, A., Von Cramon, D.Y., and Kruggel, F., 1999, Combining electrophysiological and hemodynamic measures of the auditory oddball. Psychophysiology 36:142–7.

    Article  Google Scholar 

  • Oostendorp, T.F., Delbeke, J., Stegeman, D.F., 2000, The conductivity of the human skull: results of in vivo and in vitro measurements, IEEE Trans. Biom. Eng. 47(11):1487–92.

    Article  Google Scholar 

  • Pascual-Marqui, R.D. (1995) Reply to comments by Hamalainen, Ilmoniemi and Nunez. In ISBET Newsletter N.6, December 1995. Ed: W. Skrandies., 16–28.

    Google Scholar 

  • Phillips, J.W., Leahy, R., and Mosher, J.C., 1997, MEG-based imaging of focal neuronal current sources, IEEE Trans. Med. Imag., vol. 16., n. 3, pp. 338–348.

    Article  Google Scholar 

  • Puce, A., Allison, T., Spencer, S.S., Spencer, D.D., and McCarthy, G., 1997, Comparison of cortical activation evoked by faces measured by intracranial field potentials and functional MRI: two case studies, Hum Brain Mapp 5(4):298–305.

    Article  Google Scholar 

  • Rao, C.R., and Mitra, S.K., Generalized inverse of matrices and its applications. Wiley, New York, 1977.

    Google Scholar 

  • Rosen, B., Buckner, R., and Dale, A., 1998, Event-related fMRI: past, present and future. PNAS, 95:773–780.

    Article  Google Scholar 

  • Rush S., and Driscoll, D.A., 1968, Current distribution in the brain from surface electrodes, Anesthesia Analgesia, 47:717–23.

    Article  Google Scholar 

  • Salmelin, R., Forss, N., Knuutila, J., and Hari, R., 1995, Bilateral activation of the human somatomotor cortex by distal hand movements, Electroenceph. clin. Neurophysiol. 95:444–52.

    Article  Google Scholar 

  • Sanders, J.A., Lewine, J.D., Orrison, W.W., 1996, Comparison of primary motor localization using functional magnetic resonance imaging and magnetoencephalography, Human Brain Mapping, 4:47–57.

    Article  Google Scholar 

  • Savoy, R.L., Bandettini, P.A., O’Craven, K.M., Kwong, K.K., Davis, T.L., Baker, J.R., Weisskoff, R.M., and Rosen, B.R., 1995, Proc. Soc. Magn. Reson. Med. Third Sci. Meeting Exhib. 2:450.

    Google Scholar 

  • Scherg, M., von Cramon, D., and Elton, M., 1984, Brain-stem auditory-evoked potentials in post-comatose patients after severe closed head trauma, J Neurol 231(1):1–5.

    Article  Google Scholar 

  • Scherg, M., Bast T., and Berg, P., 1999, Multiple source analysis of interictal spikes: goals, requirements, and clinical value, Journal of Neurophysiology 16:214–224.

    Article  Google Scholar 

  • Seeck, M., Lazeyras, F., Michel, C.M., Blamke, O., Gericke, C.A., Ives, J., Delavelle, J., Golay, X., Haenggeli, C.A., De Tribolet, N., and Landis, T., 1998, Non-invasive epileptic focus localization using EEG-triggered functional MRI and electromagnetic tomography, Electroenceph. and Clin. Neurophysiol. 106:508–12.

    Article  Google Scholar 

  • Shoham, D., Glaser, D.E., Arieli, A., Kenet, T., Wijnbergen, C., Toledo, Y., Hildesheim, R., and Grinvald, A., 1999, Imaging cortical dynamics at high spatial and temporal resolution with novel blue voltage-sensitive dyes, Neuron 24:791–802.

    Article  Google Scholar 

  • Sidman, R., Vincent, D., Smith, D., and Lu, L., 1992, 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. 39:437–444.

    Article  Google Scholar 

  • Spiegel, M. Theory and problems of vector analysis and an introduction to tensor analysis. Mc Graw Hill, New York, 1978.

    Google Scholar 

  • Srebro, R., Oguz, R.M., Hughlett, K., and Purdy, P.D., 1993, Estimating regional brain activity from evoked potential field on the scalp, IEEE Trans. Biom. Eng. 40:509–516.

    Article  Google Scholar 

  • Srebro, R., and Oguz, R.M., 1997, Estimating cortical activity from VEPS with the shrinking ellipsoid inverse, Electroenceph. & clin. Neurophysi.; 102:343–355.

    Article  Google Scholar 

  • Snyder, A.Z., Abdullaev, Y.G., Posner, M.I., and Raichle, M.E., 1995, Scalp electrical potentials reflect regional cerebral blood flow responses during processing of written words, Proc. Natl. Acad. Sci. USA. 92:1689–93.

    Article  Google Scholar 

  • Stok, C.J., Meijs, J.W., and Peters M.J., 1987, Inverse solutions based on MEG and EEG applied to volume conductor analysis. Phys Med Biol 32:99–104.

    Article  Google Scholar 

  • Tikhonov, A.N., and Arsenin, V.Y., Solutions of ill-posed problems. Washington D.C., Winston, 1977

    MATH  Google Scholar 

  • Uutela, K., Hämäläinen, M., and Somersalo, E., 1999, Visualization of magnetoencephalographic data using minimum current estimates, Neuroimage, 10(2):173–80.

    Article  Google Scholar 

  • van den Elsen, P.A., Pol, E.J., Viergever M., 1993, Medical image matching — A review with classification, IEEE Engineering in Medicine and Biology, 12:26–39.

    Article  Google Scholar 

  • Wagner, M., and Fuchs, M. 2001, Integration of Functional MRI, Structural MRI, EEG, and MEG, International Journal of Bioelectromagnetism, 1(3).

    Google Scholar 

  • Warach, S., Ives, J.R., Schlaug, G., Patel, M.R., Darby, D.G., Thangaraj, V., Edelman, R.R., and Schomer, D.L., 1996, EEG-triggered echo-planar functional MRI in epilepsy. Neurology 47:89–93.

    Google Scholar 

  • Wells W.M., Viola P., Atsumi H., Nakajima S., Kikinis R., 1997, Multi-modal volume registration by maximization of mutual information, Medical Image Analysis 1:35–51.

    Article  Google Scholar 

  • Wikström H., Huttunen J., Korvenoja A., Virtanen J., Salonen O., Aronen H., Ilmoniemi R.J. 1996, Effects of interstimulus interval on somatosensory evoked magnetic fields (SEFs): a hypothesis concerning SEF generation at the primary sensorimotor cortex, Electroencephalography and Clinical Neurophysiology 100(6):479–87.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dipartimento di Fisiologia Umana e Farmacologia, Università di Roma “La Sapienza”, P.le A. Moro 5, 00185, Roma, Italy

    Fabio Babiloni & Febo Cincotti

Authors
  1. Fabio Babiloni
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Febo Cincotti
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. University of Minnesota, Minneapolis, Minnesota

    Bin He

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Kluwer Academic/Plenum Publishers, New York

About this chapter

Cite this chapter

Babiloni, F., Cincotti, F. (2004). Multimodal Imaging from Neuroelectromagnetic and Functional Magnetic Resonance Recordings. In: He, B. (eds) Modeling and Imaging of Bioelectrical Activity. Bioelectric Engineering. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-49963-5_8

Download citation

  • DOI: https://doi.org/10.1007/978-0-387-49963-5_8

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-306-48112-3

  • Online ISBN: 978-0-387-49963-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation