Functional Magnetic Resonance Imaging

  • John A. Sexton
  • Gopikrishna Deshpande
  • Zhihao Li
  • Christopher B. Glielmi
  • Xiaoping P. Hu
Chapter

Abstract

Since its inception in the early 1990s, functional magnetic resonance imaging (fMRI) has evolved into a versatile and widely used technique to study the brain. This chapter provides an introduction to the principles of MRI and fMRI as well as a detailed look at the physiological source of the fMRI signal. The chapter is organized into the following sections: (1) the physics of nuclear magnetic resonance (NMR), image formation, and contrast mechanisms; (2) an overview of functional MRI; (3) fMRI experiment design; (4) fMRI data analysis; (5) biophysical modeling of the fMRI signal; (6) spatial and temporal resolution in fMRI; (7) signal and noise considerations; and (8) an introduction to combined fMRI and electroencephalography (EEG) analysis.

Keywords

Dioxide Foam Covariance Autocorrelation Convolution 

References

  1. 1.
    Raj D, Paley DP, Anderson AW, Kennan RP, Gore JC (2000) A model for susceptibility artefacts from respiration in functional echo-planar magnetic resonance imaging. Phys Med Biol 45:3809–3820CrossRefGoogle Scholar
  2. 2.
    Bandettini PA, Wong EC, Hinks RS, Tikofsky RS, Hyde JS (1992) Time course EPI of human brain function during task activation. Magn Reson Med 25:390–398CrossRefGoogle Scholar
  3. 3.
    Kwong KK, Belliveau JW, Chesler DA, Goldberg IE, Weisskoff RM, Poncelet BP, Kennedy DN, Hoppel BE, Cohen MS, Turner R (1992) Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci USA 89:5675–5679CrossRefGoogle Scholar
  4. 4.
    Ogawa S, Tank DW, Menon R, Ellermann JM, Kim SG, Merkle H, Ugurbil K (1992) Intrinsic signal chances accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci USA 89:5951–5955CrossRefGoogle Scholar
  5. 5.
    Bandettini PA (2007) Functional MRI today. Int J Physchophys 63(2):138–145Google Scholar
  6. 6.
    Craddock CR, Holtzheumer PE, Hu XP, Maybeg HS (2009) Disease state prediction from resting state functional connectivity. Magn Reson Med 62:1619–1628CrossRefGoogle Scholar
  7. 7.
    Friston KJ (1994) Functional and effective connectivity in neuroimaging: a synthesis. Hum Brain Mapp 2:56–78CrossRefGoogle Scholar
  8. 8.
    Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52:1059–1069CrossRefGoogle Scholar
  9. 9.
    Fox PT, Raichle ME (1986) Focal physiological uncoupling of cerebral blood flow and oxidative metabolism during somatosensory stimulation in human subjects. Proc Natl Acad Sci USA 83:1140–1144CrossRefGoogle Scholar
  10. 10.
    Fox PT, Raichle ME, Mintun MA, Dence C (1988) Nonoxidative glucose consumption during focal physiologic neural activity. Science 241:462–464CrossRefGoogle Scholar
  11. 11.
    Hoge RD, Atkinson J, Gill B, Crelier GR, Marrett S, Pike GB (1999) Investigation of BOLD signal dependence on cerebral blood flow and oxygen consumption: the deoxyhemoglobin dilution model. Magn Reson Med 42(5):849–863CrossRefGoogle Scholar
  12. 12.
    Lu H, Golay X, Pekar JJ, Van Zijl PC (2003) Functional magnetic resonance imaging based on changes in vascular space occupancy. Magn Reson Med 50(2):263–274CrossRefGoogle Scholar
  13. 13.
    Li CW, Wu C-W, Chen D-Y, Chen J-H (2007) Using EPI-based T1 mapping to Compare Activation Localization on Cortical Gray Matter among Three fMRI Techniques: BOLD, FAIR and VASO. Proc IFMBE 14(15):2260–2263CrossRefGoogle Scholar
  14. 14.
    Tjandra T, Brooks JC, Figueiredo P, Wise R, Matthews PM, Tracey I (2005) Quantitative assessment of the reproducibility of functional activation measured with BOLD and MR perfusion imaging: implications for clinical trial design. Neuroimage 27(2):393–401CrossRefGoogle Scholar
  15. 15.
    O’Craven KM, Rosen BR, Kwong KK, Treisman A, Savoy RL (1997) Voluntary attention modulates fMRI activity in Human MT-MST. Neuron 18:591–598CrossRefGoogle Scholar
  16. 16.
    Glover GH (1999) Deconvolution of impulse response in event-related BOLD fMRI. Neuroimage 9:416–429CrossRefGoogle Scholar
  17. 17.
    Braver TS, Barch DM, Gray JR, Molfese DL, Snyder A (2001) Anterior cingulate cortex and response conflict: effects of frequency, inhibition and errors. Cereb Cortex 11:825–836CrossRefGoogle Scholar
  18. 18.
    Amaro E, Barker GJ (2006) Study design in fMRI: basic principles. Brain Cogn 60:220–232CrossRefGoogle Scholar
  19. 19.
    Friston KJ, Williams S, Howard R, Frackowiak RS, Turner R (1996) Movement-related effects in fMRI time-series. Magn Reson Med 35(3):346–55CrossRefGoogle Scholar
  20. 20.
    Friston KJ, Josephs O, Rees G, Turner R (1998) Nonlinear event-related responses in fMRI. Magn Reson Med 39(1):41–52CrossRefGoogle Scholar
  21. 21.
    Van De Moortele PF, Pfeuffer J, Glover GH, Ugurbil K, Hu X (2002) Respiration-induced B0 fluctuations and their spatial distribution in the human brain at 7 Tesla. Magn Reson Med 47:888–895CrossRefGoogle Scholar
  22. 22.
    Jezzard P, Clare S (1999) Sources of distortion in functional MRI data. Hum Brain Mapp 8:80–85Google Scholar
  23. 23.
    Hutton C, Bork A, Josephs O, Deichmann R, Ashburner J, Turner R (2002) Image distortion correction in fMRI: a quantitative evaluation. Neuroimage 16:217–240Google Scholar
  24. 24.
    Huettel SA, Song AW, McCarthy G (2004) Functional Magnetic Resonance Imaging. Sinauer Assoc, Sunderland, MassachusettsGoogle Scholar
  25. 25.
    Menon RS (2002) Post-acquisition suppression of large-vessel BOLD signals in high-resolution fMRI. Magn Reson Med 47(1):1–9MathSciNetCrossRefGoogle Scholar
  26. 26.
    Rowe D (2005) Modeling both the magnitude and phase of complex-valued fMRI data. Neuroimage 25(4):1310–1324CrossRefGoogle Scholar
  27. 27.
    Rowe D (2005) Parameter estimation in the magnitude-only and complex-valued fMRI data models. Neuroimage 25(4):1124–1132CrossRefGoogle Scholar
  28. 28.
    Freire L, Roche A, Mangin JF (2002) What is the best similarity measure for motion correction in fMRI time series? IEEE Trans Med Imag 21(5):470–484CrossRefGoogle Scholar
  29. 29.
    Talairach J, Tournoux P (1988) Co-Planar Stereotaxic Atlas of the Human Brain. Georg Theme Verlag, Stuttgart, GermanyGoogle Scholar
  30. 30.
    Brett M, Johnsrude IS, Owen AM (2002) The problem of functional localization in the human brain. Nat Rev Neurosci 3(3):243–249CrossRefGoogle Scholar
  31. 31.
    Friston KJ, Worsley KJ, Frackowiak RSJ, Mazziotta JC, Evans AC (1993) Assessing the significance of focal activations using their spatial extent. Hum Brain Mapp 1(3):210–220CrossRefGoogle Scholar
  32. 32.
    Poline JB, Mazoyer BM (1994) Enhanced detection in brain activation maps using a multifiltering approach. J Cereb Blood Flow Metab 14(4):639–642CrossRefGoogle Scholar
  33. 33.
    Worsley KJ, Marrett S, Neelin P, Evans AC (1996) Searching scale space for activation in PET images. Hum Brain Mapp 4(1):74–90CrossRefGoogle Scholar
  34. 34.
    Friston KJ, Holmes AP, Worsley KJ, Poline JP, Frith CD, Frackowiak RSJ (1994) Statistical parametric maps in functional imaging: a general linear approach. Hum Brain Mapp 2(4):189–210CrossRefGoogle Scholar
  35. 35.
    Friston KJ, Holmes AP, Poline JB, Grasby PJ, Williams SC, Frackowiak RS, Turner R (1995) Analysis of fMRI time-series revisited. Neuroimage 2(1):45–53CrossRefGoogle Scholar
  36. 36.
    Yacoub E, Van De Moortele PFV, Shmuel A, Ugurbil K (2005) Signal and noise characteristics of Hahn SE and GE BOLD fMRI at 7 T in humans. Neuroimage 24:738–750CrossRefGoogle Scholar
  37. 37.
    Lin A-L, Fox PT, Yang Y, Lu H, Tan L-H, Gao J-H (2008) Evaluation of MRI models in the measurement of CMRO2 and its relationship with CBF. Magn Reson Med 60(2):380–389CrossRefGoogle Scholar
  38. 38.
    Grubb RL Jr, Raichle ME, Eichling JO, Ter-Pogossian MM (1974) The effects of changes in PaCO2 on cerebral blood volume, blood flow, and vascular mean trainsit time. Stroke 5:630–639CrossRefGoogle Scholar
  39. 39.
    Buxton RB, Wong EC, Frank LR (1998) Dynamics of blood flow and oxygenation changes during brain activation: the balloon model. Magn Reson Med 39:855–864CrossRefGoogle Scholar
  40. 40.
    Davis TL, Kwong KK, Weisskoff RM, Rosen BR (1998) Calibrated functional MRI: mapping the dynamics of oxidative metabolism. Proc Natl Acad Sci USA 95(4):1834–1839CrossRefGoogle Scholar
  41. 41.
    Buxton RB, Uludag K, Dubowitz DJ, Liu TT (2004) Modeling the hemodynamic response to brain activation. Neuroimage 23(Suppl 1):S220–S233CrossRefGoogle Scholar
  42. 42.
    Friston KJ, Mechelli A, Turner R, Price CJ (2000) Nonlinear responses in fMRI: the balloon model, Volterra kernels, and other hemodynamics. Neuroimage 12(4):466–477CrossRefGoogle Scholar
  43. 43.
    Sotero RC, Trujillo-Barreto NJ, Jimenez JC, Carbonell F, Rodriguez-Rojas R (2009) Identification and comparison of stochastic metabolic/hemodynamic models (sMHM) for the generation of the BOLD signal. J Comput Neurosci 26(2):251–269CrossRefGoogle Scholar
  44. 44.
    Lu H, Golay X, Pekar JJ, Van Zijl PC (2004) Sustained post-stimulus elevation in cerebral oxygen utilization after vascular recovery. J Cereb Blood Flow Metab 24(7):764–770CrossRefGoogle Scholar
  45. 45.
    Kim SG, Richter W, Ugurbil K (1997) Limitations of temporal resolution in functional MRI. Magn Reson Med 37:631–636CrossRefGoogle Scholar
  46. 46.
    Chang C, Thomason ME, Glover GH (2008) Mapping and correction of vascular hemodynamic latency in the BOLD signal. Neuroimage 43:90–102CrossRefGoogle Scholar
  47. 47.
    Kruger G, Glover GH (2001) Physiological noise in oxidative-sensitive magnetic resonance imaging. Magn Reson Med 46:631–637CrossRefGoogle Scholar
  48. 48.
    Triantafyllou C, Hoge RD, Krueger G, Wiggins CJ, Potthast A, Wiggins GC, Wald LL (2005) Comparison of physiological noise at 1.5 T, 3 T and 7 T, and optimization of fMRI acquisition parameters. Neuroimage 26:243–250CrossRefGoogle Scholar
  49. 49.
    Hu X, Le TH, Parish T, Erhard P (1995) Retrospective estimation and correction of physiological fluctuation in Functional MRI. Magn Reson Med 34:201–212CrossRefGoogle Scholar
  50. 50.
    Wowk B, McIntyre MC, Saunders JK (1997) K-space detection and correction of physiological artifacts in fMRI. Magn Reson Med 38:1029–1034Google Scholar
  51. 51.
    Biswal B, Deyoe E, Hyde JS (1996) Reduction of physiological fluctuations in fMRI using digital filters. Magn Reson Med 35:107–113Google Scholar
  52. 52.
    Glover GH, Li TQ, Ress D (2000) Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magn Reson Med 44:163–167CrossRefGoogle Scholar
  53. 53.
    Chuang KH, Chen JH (2001) IMPACT: image-based physiological artifacts estimation and correction technique for functional MRI. Magn Reson Med 46:344–353Google Scholar
  54. 54.
    Le TH, Hu X (1996) Retrospective estimation and correction of physiological artifacts in fMRI by direct extraction of physiological activity from MR data. Magn Reson Med 35:290–298Google Scholar
  55. 55.
    Heinze HJ, Mangun GR, Burchert W, Hinriches H, Scholz M, Munte TF, Gos A, Scherg M, Johannes S, Hundeshagen H, Gazzaniga MS, Hillyard SA (1994) Combined spatial and temporal imaging of brain activity during visual selective attention in humans. Nature 372:543–546CrossRefGoogle Scholar
  56. 56.
    Gotman J, Kobayashi E, Bagshaw AP, Bénar C-G, Dubeau F (2006) Combining EEG and fMRI: a multimodal tool for epilepsy research. J Magn Reson Imaging 23:906–920CrossRefGoogle Scholar
  57. 57.
    Gonzalez Andino SL, Blanke O, Lantz G, Thut G, GravedePeraltaMenendez R (2001) The use of functional constraints for the neuroelectromagnetic inverse problem: alternatives and caveats. Int J Bioelectromagn 3(1)Google Scholar
  58. 58.
    Arthurs OJ, Boniface SJ (2003) What aspect of the fMRI BOLD signal best reflects the underlying electrophysiology in human somatosensory cortex? Clin Neurophysiol 114:1203–1209CrossRefGoogle Scholar
  59. 59.
    Nunez PL, Silberstein RB (2000) On the relationship of synaptic activity to macroscopic measurements: does co-registration of EEG with fMRI make sense? Brain Topogr 13:79–96CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • John A. Sexton
    • 1
  • Gopikrishna Deshpande
    • 2
  • Zhihao Li
    • 1
  • Christopher B. Glielmi
    • 3
  • Xiaoping P. Hu
    • 1
  1. 1.Coulter Department of Biomedical EngineeringGeorgia Tech and Emory UniversityAtlantaUSA
  2. 2.Department of Electrical and Computer EngineeringAuburn UniversityAuburnUSA
  3. 3.Siemens HealthcareMR Research and DevelopmentChicagoUSA

Personalised recommendations