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Noninvasive Neurophysiological Imaging with Magnetoencephalography

  • Tony W. WilsonEmail author
Protocol
  • 3.9k Downloads
Part of the Springer Protocols Handbooks book series (SPH)

Abstract

Magnetoencephalography (MEG) is a noninvasive neurophysiological recording technique that is primarily utilized in human studies of system-level brain function. Although the seminal MEG measurements occurred more than 40 years ago, the precision of the instruments and the analytical sophistication of the field have dramatically increased over the past decade. At present, MEG is the only noninvasive high-resolution neurophysiological imaging technique and the only functional brain imaging method to offer both high temporal (<1 ms) and spatial (2–5 mm) resolution. The current chapter will provide a brief historical introduction to MEG and functional magnetic resonance imaging (fMRI), which is the most common method of functional brain imaging. Description of the physical and physiological bases of the signals measured in noninvasive functional imaging will follow, with an emphasis on the neuromagnetic signals quantified in human MEG measurements. An introduction to the most common MEG analysis methods will be presented; and thereafter, several examples of MEG applications will be discussed to illustrate the type of questions often pursued in MEG research and the general areas of study where MEG measurements are making an impact. The chapter will conclude by presenting some new applications for MEG-based functional brain imaging.

Keywords

Electrophysiology Oscillations MEG Gamma Beta Neuroimaging Synchronization Desynchronization Synchrony Cortex 

References

  1. Ahonen AI, Hamalainen MS, Kajola MJ, Knuutila JET, Laine PP, Lounasmaa OV, Parkkonen LT, Simola JT, Tesche CD (1993) 122-channel SQUID instrument for investigating the magnetic signals from the human brain. Physica Scripta T49:198–205CrossRefGoogle Scholar
  2. Aubert A, Pellerin L, Magistretti PJ, Costalat R (2007) A coherent neurobiological framework for functional neuroimaging provided by a model integrating compartmentalized energy metabolism. Proc Natl Acad Sci U S A 104:4188–4193CrossRefPubMedPubMedCentralGoogle Scholar
  3. Baillet S (2010) The dowser in the fields: searching for MEG sources. In: Hansen PC, Kringelbach ML, Salmelin R (eds) MEG: an introduction to the methods. Oxford University Press, New York, pp 83–123CrossRefGoogle Scholar
  4. Baillet S, Mosher JC, Leahy RM (2001) Electromagnetic brain mapping. IEEE Signal Process Mag 18(6):14–30CrossRefGoogle Scholar
  5. Bandettini PA, Ungerleider LG (2001) From neuron to BOLD: new connections. Nat Neurosci 4:864–866CrossRefPubMedGoogle Scholar
  6. Bandettini PA, Wong EC, Hinks RS, Tikofsky RS, Hyde JS (1992) Time course EPI of human brain function during task activation. Magn Reson Med 25:390–397CrossRefPubMedGoogle Scholar
  7. Cohen DS (1968) Magnetoencephalography: evidence of magnetic fields produced by alpha rhythm currents. Science 161:784–786CrossRefPubMedGoogle Scholar
  8. Goense JB, Logothetis NK (2008) Neurophysiology of the BOLD fMRI signal in awake monkeys. Curr Biol 18:631–640CrossRefPubMedGoogle Scholar
  9. Hämäläinen MS, Ilmoniemi RJ (1994) Interpreting magnetic fields of the brain: minimum norm estimates. Med Biol Eng Comput 32(1):35–42CrossRefPubMedGoogle Scholar
  10. Hämäläinen MS, Sarvas J (1989) Realistic conductivity geometry model of the human head for interpretation of neuromagnetic data. IEEE Trans Biomed Eng 36(2):165–171CrossRefPubMedGoogle Scholar
  11. Hämäläinen M, Hari R, Ilmoniemi RJ, Knuutila J, Lounasmaa OV (1993) Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain. Rev Mod Phys 65(2):413–495CrossRefGoogle Scholar
  12. Hansen PC, Kringelbach ML, Salmelin R (eds) (2010) MEG: an introduction to the methods. Oxford University Press, New YorkGoogle Scholar
  13. Heeger DJ, Rees D (2002) What does fMRI tell us about neuronal activity? Nat Rev Neurosci 3:142–151CrossRefPubMedGoogle Scholar
  14. Heeger DJ, Huk AC, Geisler WS, Albrecht DG (2000) Spikes versus BOLD: what does neuroimaging tell us about neuronal activity? Nat Neurosci 3:631–633CrossRefPubMedGoogle Scholar
  15. Hillebrand A, Barnes GR (2002) A quantitative assessment of the sensitivity of whole-head MEG to activity in the adult human cortex. Neuroimage 16:638–650CrossRefPubMedGoogle Scholar
  16. Hillebrand A, Singh KD, Holliday IE, Furlong PL, Barnes GR (2005) A new approach to neuroimaging with magnetoencephalography. Hum Brain Mapp 25:199–211CrossRefPubMedGoogle Scholar
  17. Huettel SA, Song AW, McCarthy G (2008) Functional magnetic resonance imaging, 2nd edn. Sinauer, Sunderland, MAGoogle Scholar
  18. Humm JL, Rosenfeld A, Del Guerra A (2003) From PET detectors to PET scanners. Eur J Nucl Med Mol Imaging 30:1574–1597CrossRefPubMedGoogle Scholar
  19. Kwong KK, Belliveau JW, Chesler DA, Goldberg IE, Weisskoff RM, Poncelet BP et al (1992) Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci U S A 89:5675–5679CrossRefPubMedPubMedCentralGoogle Scholar
  20. Leahy RM, Mosher JC, Spencer ME, Huang MX, Lewine JD (1998) A study of dipole localization accuracy for MEG and EEG using a human skull phantom. Clin Neurophysiol 107:159–173CrossRefGoogle Scholar
  21. Logothetis NK (2003) The underpinnings of the BOLD functional magnetic resonance imaging signal. J Neurosci 23:3963–3971PubMedGoogle Scholar
  22. Logothetis NK, Pauls J, Augath M, Trinath T, Oeltermann A (2001) Neurophysiological investigation of the basis of the fMRI signal. Nature 412:150–157CrossRefPubMedGoogle Scholar
  23. Lopes da Silva FH (2010) Electrophysiological basis of MEG signals. In: Hansen PC, Kringelbach ML, Salmelin R (eds) MEG: an introduction to the methods. Oxford University Press, New York, pp 1–23Google Scholar
  24. Lopes da Silva FH, van Rotterdam A (2005) Biophysical aspects of EEG and magnetoencephalographic generation. In: Niedermeyer E, Lopes da Silva FH (eds) Electroencephalography, basic principles, clinical applications and related fields, 5th edn. Lippincott Williams & Wilkins, Philadelphia, pp 1165–1198Google Scholar
  25. Lu ZL, Kaufman L (eds) (2003) Magnetic source imaging of the human brain. Lawrence Erlbaum Associates, Mahwah, NJGoogle Scholar
  26. Magistretti PJ, Pellerin L (1999) Astrocytes couple synaptic activity to glucose utilization in the brain. News Physiol Sci 14:177–182PubMedGoogle Scholar
  27. Mosher JC, Baillet S, Leahy RM (1999) EEG source localization and imaging using multiple signal classification approaches. J Clin Neurophysiol 16(3):225–238CrossRefPubMedGoogle Scholar
  28. Murakami S, Okada Y (2006) Contributions of principal neocortical neurons to magnetoencephalography and electroencephalography signals. J Physiol 575:925–936CrossRefPubMedPubMedCentralGoogle Scholar
  29. Ogawa S, Lee TM, Kay AR, Tank DW (1990) Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc Natl Acad Sci U S A 87:9868–9872CrossRefPubMedPubMedCentralGoogle Scholar
  30. Ogawa S, Tank DW, Menon R, Ellermann JM, Kim SG, Merkle H et al (1992) Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci U S A 89:5951–5955CrossRefPubMedPubMedCentralGoogle Scholar
  31. Okada YC, Wu J, Kyuhou S (1997) Genesis of MEG signals in a mammalian CNS structure. Clin Neurophysiol 103:474–485CrossRefGoogle Scholar
  32. Parkkonen L (2010) Instrumentation and data processing. In: Hansen PC, Kringelbach ML, Salmelin R (eds) MEG: an introduction to the methods. Oxford University Press, New York, pp 24–64CrossRefGoogle Scholar
  33. Raichle ME, Mintun MA (2006) Brain work and brain imaging. Annu Rev Neurosci 29:449–476CrossRefPubMedGoogle Scholar
  34. Rees G, Friston K, Koch C (2000) A direct quantitative relationship between the functional properties of human and macaque V5. Nat Neurosci 3:716–723CrossRefPubMedGoogle Scholar
  35. Sarvas J (1987) Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem. Phys Med Biol 32(1):11–22CrossRefPubMedGoogle Scholar
  36. van Veen BD, van Drongelen W, Yuchtman M, Suzuki A (1997) Localization of brain electrical activity via linearly constrained minimum variance spatial filtering. IEEE Trans Biomed Eng 44:867–880CrossRefPubMedGoogle Scholar
  37. Vrba J, Robinson S (2001) Signal processing in magnetoencephalography. Methods 25:249–271CrossRefPubMedGoogle Scholar
  38. Wagner H, Eiselt M, Zwienger U (1997) Exactness of source analysis of biomagnetic signals of epileptiform spikes by the method of spatial filtering: a computer simulation. Med Biol Eng Comput 35:708–714CrossRefPubMedGoogle Scholar
  39. Wilson TW, Slason E, Hernandez OO, Asherin RM, Reite ML, Teale PD, Rojas DC (2009) Aberrant high frequency desynchronization of cerebellar cortices in early-onset psychosis. Psychiatry Res 174:47–56CrossRefPubMedPubMedCentralGoogle Scholar
  40. Wilson TW, Slason E, Asherin RM, Kronberg E, Reite ML, Teale PD, Rojas DC (2010) An extended motor network generates beta and gamma oscillatory perturbations during development. Brain Cogn 73:75–84CrossRefPubMedPubMedCentralGoogle Scholar
  41. Wilson TW, Slason E, Asherin RM, Kronberg E, Teale PD, Reite ML, Rojas DC (2011) Abnormal gamma and beta MEG activity during finger movements in early-onset psychosis. Dev Neuropsychol 36:596–613CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Pharmacology and Experimental NeuroscienceUniversity of Nebraska Medical Center (UNMC)OmahaUSA
  2. 2.Center for MagnetoencephalographyUniversity of Nebraska Medical CenterOmahaUSA
  3. 3.Department of Neurological SciencesUniversity of Nebraska Medical Center (UNMC)OmahaUSA
  4. 4.Munroe-Meyer Institute for Genetics and RehabilitationUniversity of Nebraska Medical Center (UNMC)OmahaUSA

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