Introduction to Brain Imaging

Chapter
Part of the Biological and Medical Physics, Biomedical Engineering book series (BIOMEDICAL)

Abstract

Anatomical landmarks are useful in describing the location of different functional brain regions, for example, the primary sensorimotor cortex in the pre- and post-central sulci, the primary auditory cortex on Heschl’s gyrus, and the primary visual cortex in the calcarine sulcus [1]. However, early studies examining the effects of different brain lesions on function, and the advent of neuroimaging, have shown that there is tremendous intraindividual variability in both the structure and functional organization of the human brain. Like fingerprints, each brain has a unique configuration of gyri and sulci (crests and troughs, respectively, in the surface of the brain) [2, 3]. In addition, brain function may not be specifically localized with respect to sulcal neuroanatomy, prompting the conclusion that sulci are not generally valid landmarks of the microstructural organization of the cortex [4]. In patients with brain pathology, the use of anatomical landmarks can further be jeopardized due to edema or mass effects that obliterate the structure of gyri and sulci and can induce plasticity in functional organization. These findings highlight the important role of personalized structural and functional neuroimaging, especially for clinical applications such as presurgical brain mapping. In this chapter, the chief neuroimaging methods relevant to the diagnosis and management of patients with brain tumor or epilepsy are reviewed.

Keywords

Diffusion Tensor Imaging Bold Signal Brain Tumor Patient Cortical Stimulation Brain Shift 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The image data shown in Figs. 3.13.3 were collected at the National Research Council Institute for Biodiagnostics (NRC-IBD) from patients treated in the Neurosurgery Department of the Health Science Center (HSC) in Winnipeg. The author would like to thank Dr. Michael West, Head of the Neurosurgery Department at HSC, and Dr. Owen Williams from the same Department, for their involvement in referring patients and interpreting the image data shown in the figures in this chapter, and Dr. Uta Sboto-Frankenstein and Dr. Jordan Hovdebo from NRC-IBD for their assistance in collecting and analyzing the images.

References

  1. 1.
    Naidich, T.P., Valavanis, A.G., Kubik, S.: Anatomic relationships along the low-middle ­convexity: part I–Normal specimens and magnetic resonance imaging. Neurosurgery 36, 517–532 (1995)Google Scholar
  2. 2.
    Mazziotta, J.C., Toga, A.W., Evans, A., et al.: A probabilistic atlas of the human brain: theory and rationale for its development. The International Consortium for Brain Mapping (ICBM). Neuroimage 2, 89–101 (1995)Google Scholar
  3. 3.
    Toga, A.W., Thompson, P.M., Mori, S., et al.: Towards multimodal atlases of the human brain. Nat. Rev. Neurosci. 7, 952–966 (2006)Google Scholar
  4. 4.
    Zilles, K., Schleicher, A., Langemann, C., et al.: Quantitative analysis of sulci in the human cerebral cortex: development, regional ­heterogeneity, gender difference, asymmetry, intersubject variability and cortical architecture. Hum. Brain Mapp. 5, 218–221 (1997)Google Scholar
  5. 5.
    Lauterbur, P.C.: Image formation by induced local interactions. Examples employing nuclear magnetic resonance. Nature 242, 190–191 (1973)ADSGoogle Scholar
  6. 6.
    Mansfield, P., Maudsley, A.A.: Medical imaging by NMR. Br. J. Radiol. 50, 188–194 (1977)Google Scholar
  7. 7.
    Albert, F.K., Forsting, M., Sartor, K., et al.: Early postoperative magnetic resonance imaging after resection of malignant glioma: objective evaluation of residual tumor and its influence on regrowth and prognosis. Neurosurgery 34, 45–60 (1994)Google Scholar
  8. 8.
    Ogawa, S., Lee, T.M., Kay, A.R., et al.: Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc. Natl. Acad. Sci. U.S.A. 87, 9868–9872 (1990)ADSGoogle Scholar
  9. 9.
    Kwong, K.K., Belliveau, J.W., Chesler, D.A., et al.: Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc. Natl. Acad. Sci. U.S.A. 89, 5675–5679 (1992)ADSGoogle Scholar
  10. 10.
    Belliveau, J.W., Kennedy Jr., D.N., McKinstry, R.C., et al.: Functional mapping of the human visual cortex by magnetic resonance imaging. Science 254, 716–719 (1991)ADSGoogle Scholar
  11. 11.
    Ogawa, S., Tank, D.W., Menon, R., et al.: Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc. Natl. Acad. Sci. U.S.A. 89, 5951–5955 (1992)ADSGoogle Scholar
  12. 12.
    Bandettini, P.A., Wong, E.C., Hinks, R.S., et al.: Time course EPI of human brain function during task activation. Magn. Reson. Med. 25, 390–397 (1992)Google Scholar
  13. 13.
    Mesulam, M.M.: From sensation to cognition. Brain 121(pt 6), 1013–1052 (1998)Google Scholar
  14. 14.
    Bookheimer, S.: Pre-surgical language mapping with functional magnetic resonance imaging. Neuropsychol. Rev. 17, 145–155 (2007)Google Scholar
  15. 15.
    Binder, J.R., Swanson, S.J., Hammeke, T.A., et al.: A comparison of five fMRI protocols for mapping speech comprehension systems. Epilepsia 49, 1980–1997 (2008)Google Scholar
  16. 16.
    Aguirre, G.K., D’Esposito, M.: Experimental design for brain fMRI. In: Moonen, C.T., Bandettini, P. (eds.) Functional MRI, pp. 369–380. Springer, Berlin (1999)Google Scholar
  17. 17.
    Price, C.J., Friston, K.J.: Cognitive conjunction: a new approach to brain activation experiments. Neuroimage 5, 261–270 (1997)Google Scholar
  18. 18.
    Buckner, R.L., Braver, T.S.: Event-related functional MRI. In: Moonen, C.T., Bandettini, P. (eds.) Functional MRI, pp. 441–452. Springer, Berlin (1999)Google Scholar
  19. 19.
    Voyvodic, J.T.: Activation mapping as a percentage of local excitation: fMRI stability within scans, between scans and across field strengths. Magn. Reson. Imaging 24, 1249–1261 (2006)Google Scholar
  20. 20.
    Voyvodic, J.T., Petrella, J.R., Friedman, A.H.: fMRI activation mapping as a percentage of local excitation: consistent presurgical motor maps without threshold adjustment. J. Magn. Reson. Imaging 29, 751–759 (2009)Google Scholar
  21. 21.
    Basser, P.J., Pierpaoli, C.: Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J. Magn. Reson. B 111, 209–219 (1996)Google Scholar
  22. 22.
    Pierpaoli, C., Jezzard, P., Basser, P.J., et al.: Diffusion tensor MR imaging of the human brain. Radiology 201, 637–648 (1996)Google Scholar
  23. 23.
    Mori, S., van Zijl, P.C.: Fiber tracking: principles and strategies – a technical review. NMR Biomed. 15, 468–480 (2002)Google Scholar
  24. 24.
    Moseley, M.E., Cohen, Y., Kucharczyk, J., et al.: Diffusion-weighted MR imaging of anisotropic water diffusion in cat central nervous system. Radiology 176, 439–445 (1990)Google Scholar
  25. 25.
    Papadakis, N.G., Murrills, C.D., Hall, L.D., et al.: Minimal gradient encoding for robust estimation of diffusion anisotropy. Magn. Reson. Imaging 18, 671–679 (2000)Google Scholar
  26. 26.
    Douek, P., Turner, R., Pekar, J., et al.: MR color mapping of myelin fiber orientation. J. Comput. Assist. Tomogr. 15, 923–929 (1991)Google Scholar
  27. 27.
    Basser, P.J., Pajevic, S., Pierpaoli, C., et al.: In vivo fiber tractography using DT-MRI data. Magn. Reson. Med. 44, 625–632 (2000)Google Scholar
  28. 28.
    Mori, S., Crain, B.J., Chacko, V.P., et al.: Three-dimensional tracking of axonal ­projections in the brain by magnetic resonance imaging. Ann. Neurol. 45, 265–269 (1999)Google Scholar
  29. 29.
    Cohen, D.: Magnetoencephalography: detection of the brain’s electrical activity with a superconducting magnetometer. Science 175, 664–666 (1972)ADSGoogle Scholar
  30. 30.
    Cohen, D.: Magnetoencephalography: evidence of magnetic fields produced by alpha-rhythm currents. Science 161, 784–786 (1968)ADSGoogle Scholar
  31. 31.
    Nunez, P.L.: Electric Fields of the Brain: The Neurophysics of EEG. Oxford University Press, New York (1981)Google Scholar
  32. 32.
    Hillebrand, A., Barnes, G.R.: A quantitative assessment of the sensitivity of whole-head MEG to activity in the adult human cortex. Neuroimage 16, 638–650 (2002)Google Scholar
  33. 33.
    Stok, C.J., Meijs, J.W., Peters, M.J.: Inverse solutions based on MEG and EEG applied to volume conductor analysis. Phys. Med. Biol. 32, 99–104 (1987)Google Scholar
  34. 34.
    Baillet, S., Garnero, L., Marin, G., et al.: Combined MEG and EEG source imaging by minimization of mutual information. IEEE Trans. Biomed. Eng. 46, 522–534 (1999)Google Scholar
  35. 35.
    Galambos, R., Sheatz, G.C.: An electroencephalograph study of classical conditioning. Am. J. Physiol. 203, 173–184 (1962)Google Scholar
  36. 36.
    Walter, W.G., Cooper, R., Aldridge, V.J., et al.: Contingent negative variation: and electric sign of sensorimotor association and expectancy in the human brain. Nature 203, 380­–384 (1964)Google Scholar
  37. 37.
    Halliday, A.M.: Evoked Potentials in Clinical Testing. Churchill Livingtsone, Edinburgh (1993)Google Scholar
  38. 38.
    Aminoff, M.J., Eisen, A.A.: AAEM minimonograph 19: somatosensory evoked potentials. Muscle Nerve 21, 277–290 (1998)Google Scholar
  39. 39.
    Ives, J.R., Warach, S., Schmitt, F., et al.: Monitoring the patient’s EEG during echo planar MRI. Electroencephalogr. Clin. Neurophysiol. 87, 417–420 (1993)Google Scholar
  40. 40.
    Laufs, H., Daunizeau, J., Carmichael, D.W., et al.: Recent advances in recording electrophysiological data simultaneously with magnetic resonance imaging. Neuroimage 40, 515–528 (2008)Google Scholar
  41. 41.
    Liebenthal, E., Ellingson, M.L., Spanaki, M.V., et al.: Simultaneous ERP and fMRI of the auditory cortex in a passive oddball paradigm. Neuroimage 19, 1395–1404 (2003)Google Scholar
  42. 42.
    Liebenthal, E., Desai, R., Ellingson, M.M., et al.: Specialization along the left superior temporal sulcus for auditory categorization. Cereb. Cortex 20, 2958–2970 (2010)Google Scholar
  43. 43.
    Horovitz, S.G., Skudlarski, P., Gore, J.C.: Correlations and dissociations between BOLD signal and P300 amplitude in an auditory oddball task: a parametric approach to combining fMRI and ERP. Magn. Reson. Imaging 20, 319–325 (2002)Google Scholar
  44. 44.
    Ellingson, M.L., Liebenthal, E., Spanaki, M.V., et al.: Ballistocardiogram artifact reduction in the simultaneous acquisition of auditory ERPS and fMRI. Neuroimage 22, 1534–1542 (2004)Google Scholar
  45. 45.
    Schomer, D.L., Bonmassar, G., Lazeyras, F., et al.: EEG-Linked functional magnetic resonance imaging in epilepsy and cognitive neurophysiology. J. Clin. Neurophysiol. 17, 43–58 (2000)Google Scholar
  46. 46.
    Lemieux, L., Allen, P.J., Franconi, F., et al.: Recording of EEG during fMRI experiments: patient safety. Magn. Reson. Med. 38, 943–952 (1997)Google Scholar
  47. 47.
    Bonmassar, G., Purdon, P.L., Jaaskelainen, I.P., et al.: Motion and ballistocardiogram artifact removal for interleaved recording of EEG and EPs during MRI. Neuroimage 16, 1127–1141 (2002)Google Scholar
  48. 48.
    Gotman, J., Kobayashi, E., Bagshaw, A.P., et al.: Combining EEG and fMRI: a multimodal tool for epilepsy research. J. Magn. Reson. Imaging 23, 906–920 (2006)Google Scholar
  49. 49.
    Laufs, H., Duncan, J.S.: Electroencephalography/functional MRI in human epilepsy: what it currently can and cannot do. Curr. Opin. Neurol. 20, 417–423 (2007)Google Scholar
  50. 50.
    Vlieger, E.J., Majoie, C.B., Leenstra, S., et al.: Functional magnetic resonance imaging for neurosurgical planning in neurooncology. Eur. Radiol. 14, 1143–1153 (2004)Google Scholar
  51. 51.
    Keles, G.E., Lamborn, K.R., Berger, M.S.: Low-grade hemispheric gliomas in adults: a critical review of extent of resection as a factor influencing outcome. J. Neurosurg. 95, 735–745 (2001)Google Scholar
  52. 52.
    Spencer, S., Huh, L.: Outcomes of epilepsy surgery in adults and children. Lancet Neurol. 7, 525–537 (2008)Google Scholar
  53. 53.
    Duncan, J.S.: Imaging in the surgical treatment of epilepsy. Nat. Rev. Neurol. 6, 537–550 (2010)Google Scholar
  54. 54.
    Carmichael, D.W., Thornton, J.S., Rodionov, R., et al.: Safety of localizing epilepsy monitoring intracranial electroencephalograph electrodes using MRI: radiofrequency-induced heating. J. Magn. Reson. Imaging 28, 1233–1244 (2008)Google Scholar
  55. 55.
    Salamon, N., Kung, J., Shaw, S.J., et al.: FDG-PET/MRI coregistration improves detection of cortical dysplasia in patients with epilepsy. Neurology 71, 1594–1601 (2008)Google Scholar
  56. 56.
    Lee, K.K., Salamon, N.: [18F] fluorodeoxyglucose-positron-emission tomography and MR imaging coregistration for presurgical evaluation of medically refractory epilepsy. AJNR Am. J. Neuroradiol. 30, 1811–1816 (2009)Google Scholar
  57. 57.
    Bradley, W.G.: Achieving gross total resection of brain tumors: intraoperative MR imaging can make a big difference. AJNR Am. J. Neuroradiol. 23, 348–349 (2002)Google Scholar
  58. 58.
    Albayrak, B., Samdani, A.F., Black, P.M.: Intra-operative magnetic resonance imaging in neurosurgery. Acta Neurochir. (Wien) 146, 543–556 (2004)Google Scholar
  59. 59.
    Merkle, E.M., Lewin, J.S., Liebenthal, R., et al.: The interventional MR imaging suite: magnet designs and equipment requirements. Magn. Reson. Imaging Clin. N. Am. 13, 401–413 (2005)Google Scholar
  60. 60.
    Nimsky, C., Ganslandt, O., Buchfelder, M., et al.: Glioma surgery evaluated by intraoperative low-field magnetic resonance imaging. Acta Neurochir. Suppl. 85, 55–63 (2003)Google Scholar
  61. 61.
    Black, P.M., Alexander III, E., Martin, C., et al.: Craniotomy for tumor treatment in an intraoperative magnetic resonance imaging unit. Neurosurgery 45, 423–431 (1999)Google Scholar
  62. 62.
    Schneider, J.P., Schulz, T., Schmidt, F., et al.: Gross-total surgery of supratentorial low-grade gliomas under intraoperative MR guidance. AJNR Am. J. Neuroradiol. 22, 89–98 (2001)Google Scholar
  63. 63.
    Nimsky, C., Ganslandt, O., Buchfelder, M., et al.: Intraoperative visualization for resection of gliomas: the role of functional neuronavigation and intraoperative 1.5 T MRI. Neurol. Res. 28, 482–487 (2006)Google Scholar
  64. 64.
    Hartkens, T., Hill, D.L., Castellano-Smith, A.D., et al.: Measurement and analysis of brain deformation during neurosurgery. IEEE Trans. Med. Imaging 22, 82–92 (2003)Google Scholar
  65. 65.
    Nimsky, C., Ganslandt, O., Cerny, S., et al.: Quantification of, visualization of, and compensation for brain shift using intraoperative magnetic resonance imaging. Neurosurgery 47, 1070–1079 (2000)Google Scholar
  66. 66.
    Nabavi, A., Black, P.M., Gering, D.T., et al.: Serial intraoperative magnetic resonance imaging of brain shift. Neurosurgery 48, 787–797 (2001)Google Scholar
  67. 67.
    Keles, G.E., Lamborn, K.R., Berger, M.S.: Coregistration accuracy and detection of brain shift using intraoperative sononavigation during resection of hemispheric tumors. Neurosurgery 53, 556–562 (2003)Google Scholar
  68. 68.
    Schwartz, R.B., Hsu, L., Wong, T.Z., et al.: Intraoperative MR imaging guidance for intracranial neurosurgery: experience with the first 200 cases. Radiology 211, 477–488 (1999)Google Scholar
  69. 69.
    Archip, N., Clatz, O., Whalen, S., et al.: Non-rigid alignment of pre-operative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery. Neuroimage 35, 609–624 (2007)Google Scholar
  70. 70.
    Warfield, S.K., Haker, S.J., Talos, I.F., et al.: Capturing intraoperative deformations: research experience at Brigham and Women’s Hospital. Med. Image Anal. 9, 145–162 (2005)Google Scholar
  71. 71.
    Wittek, A., Joldes, G., Couton, M., et al.: Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time; application to non-rigid neuroimage registration. Prog. Biophys. Mol. Biol. 103, 292–303 (2010)Google Scholar
  72. 72.
    Petrella, J.R., Shah, L.M., Harris, K.M., et al.: Preoperative functional MR imaging localization of language and motor areas: effect on therapeutic decision making in patients with potentially resectable brain tumors. Radiology 240, 793–802 (2006)Google Scholar
  73. 73.
    Van Westen, D., Skagerberg, G., Olsrud, J., et al.: Functional magnetic resonance imaging at 3T as a clinical tool in patients with intracranial tumors. Acta Radiol. 46, 599–609 (2005)Google Scholar
  74. 74.
    Ulmer, J.L., Hacein-Bey, L., Mathews, V.P., et al.: Lesion-induced pseudo-dominance at functional magnetic resonance imaging: implications for preoperative assessments. Neurosurgery 55, 569–579 (2004)Google Scholar
  75. 75.
    Duffau, H., Lopes, M., Arthuis, F., et al.: Contribution of intraoperative electrical stimulations in surgery of low grade gliomas: a comparative study between two series without (1985-96) and with (1996-2003) functional mapping in the same institution. J. Neurol. Neurosurg. Psychiatry 76, 845–851 (2005)Google Scholar
  76. 76.
    Haglund, M.M., Berger, M.S., Shamseldin, M., et al.: Cortical localization of temporal lobe language sites in patients with gliomas. Neurosurgery 34, 567–576 (1994)Google Scholar
  77. 77.
    Sunaert, S.: Presurgical planning for tumor resectioning. J. Magn. Reson. Imaging 23, 887–905 (2006)Google Scholar
  78. 78.
    Rutten, G.J., Ramsey, N.F.: The role of functional magnetic resonance imaging in brain surgery. Neurosurg. Focus 28, E4 (2010)Google Scholar
  79. 79.
    Upadhyay, U.M., Golby, A.J.: Role of pre- and intraoperative imaging and neuronavigation in neurosurgery. Expert Rev. Med. Devices 5, 65–73 (2008)Google Scholar
  80. 80.
    Holodny, A.I., Schulder, M., Liu, W.C., et al.: The effect of brain tumors on BOLD functional MR imaging activation in the adjacent motor cortex: implications for image-guided neurosurgery. AJNR Am. J. Neuroradiol. 21, 1415–1422 (2000)Google Scholar
  81. 81.
    Ulmer, J.L., Krouwer, H.G., Mueller, W.M., et al.: Pseudo-reorganization of language cortical function at fMR imaging: a consequence of tumor-induced neurovascular uncoupling. AJNR Am. J. Neuroradiol. 24, 213–217 (2003)Google Scholar
  82. 82.
    Desmond, J.E., Annabel Chen, S.H.: Ethical issues in the clinical application of fMRI: factors affecting the validity and interpretation of activations. Brain Cogn. 50, 482–497 (2002)Google Scholar
  83. 83.
    Binder, J.R.: Functional MRI is a valid noninvasive alternative to Wada testing. Epilepsy Behav. 20, 214–222 (2011)Google Scholar
  84. 84.
    Krainik, A., Duffau, H., Capelle, L., et al.: Role of the healthy hemisphere in recovery after resection of the supplementary motor area. Neurology 62, 1323–1332 (2004)Google Scholar
  85. 85.
    Achten, E., Jackson, G.D., Cameron, J.A., et al.: Presurgical evaluation of the motor hand area with functional MR imaging in patients with tumors and dysplastic lesions. Radiology 210, 529–538 (1999)Google Scholar
  86. 86.
    De Tiege, X., Connelly, A., Liegeois, F., et al.: Influence of motor functional magnetic resonance imaging on the surgical management of children and adolescents with symptomatic focal epilepsy. Neurosurgery 64, 856–864 (2009)Google Scholar
  87. 87.
    Haberg, A., Kvistad, K.A., Unsgard, G., et al.: Preoperative blood oxygen level-dependent functional magnetic resonance imaging in patients with primary brain tumors: clinical application and outcome. Neurosurgery 54, 902–914 (2004)Google Scholar
  88. 88.
    Mueller, W.M., Yetkin, F.Z., Hammeke, T.A., et al.: Functional magnetic resonance imaging mapping of the motor cortex in patients with cerebral tumors. Neurosurgery 39, 515–520 (1996)Google Scholar
  89. 89.
    Pujol, J., Conesa, G., Deus, J., et al.: Clinical application of functional magnetic resonance imaging in presurgical identification of the central sulcus. J. Neurosurg. 88, 863–869 (1998)Google Scholar
  90. 90.
    Lehericy, S., Duffau, H., Cornu, P., et al.: Correspondence between functional magnetic resonance imaging somatotopy and individual brain anatomy of the central region: comparison with intraoperative stimulation in patients with brain tumors. J. Neurosurg. 92, 589–598 (2000)Google Scholar
  91. 91.
    Bartos, R., Jech, R., Vymazal, J., et al.: Validity of primary motor area localization with fMRI versus electric cortical stimulation: a comparative study. Acta Neurochir. (Wien) 151, 1071–1080 (2009)Google Scholar
  92. 92.
    Hirsch, J., Ruge, M.I., Kim, K.H., et al.: An integrated functional magnetic resonance imaging procedure for preoperative mapping of cortical areas associated with tactile, motor, language, and visual functions. Neurosurgery 47, 711–721 (2000)Google Scholar
  93. 93.
    Jack Jr., C.R., Thompson, R.M., Butts, R.K., et al.: Sensory motor cortex: correlation of presurgical mapping with functional MR imaging and invasive cortical mapping. Radiology 190, 85–92 (1994)Google Scholar
  94. 94.
    Krishnan, R., Raabe, A., Hattingen, E., et al.: Functional magnetic resonance imaging-integrated neuronavigation: correlation between lesion-to-motor cortex distance and outcome. Neurosurgery 55, 904–914 (2004)Google Scholar
  95. 95.
    Pujol, J., Conesa, G., Deus, J., et al.: Presurgical identification of the primary sensorimotor cortex by functional magnetic resonance imaging. J. Neurosurg. 84, 7–13 (1996)Google Scholar
  96. 96.
    Yetkin, F.Z., Mueller, W.M., Morris, G.L., et al.: Functional MR activation correlated with intraoperative cortical mapping. AJNR Am. J. Neuroradiol. 18, 1311–1315 (1997)Google Scholar
  97. 97.
    Yousry, T.A., Schmid, U.D., Alkhadi, H., et al.: Localization of the motor hand area to a knob on the precentral gyrus. A new landmark. Brain 120, 141–157 (1997)Google Scholar
  98. 98.
    Mikuni, N., Okada, T., Enatsu, R., et al.: Clinical impact of integrated functional neuronavigation and subcortical electrical stimulation to preserve motor function during resection of brain tumors. J. Neurosurg. 106, 593–598 (2007)Google Scholar
  99. 99.
    Sereno, M.I., Dale, A.M., Reppas, J.B., et al.: Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging. Science 268, 889–893 (1995)ADSGoogle Scholar
  100. 100.
    DeYoe, E.A., Carman, G.J., Bandettini, P., et al.: Mapping striate and extrastriate visual areas in human cerebral cortex. Proc. Natl. Acad. Sci. U.S.A. 93, 2382–2386 (1996)ADSGoogle Scholar
  101. 101.
    Binder, J.R., Frost, J.A., Hammeke, T.A., et al.: Human brain language areas identified by functional magnetic resonance imaging. J. Neurosci. 17, 353–362 (1997)Google Scholar
  102. 102.
    Binder, J.R., Desai, R.H., Graves, W.W., et al.: Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cereb. Cortex 19, 2767–2796 (2009)Google Scholar
  103. 103.
    Damasio, H., Grabowski, T.J., Tranel, D., et al.: A neural basis for lexical retrieval. Nature 380, 499–505 (1996)ADSGoogle Scholar
  104. 104.
    Demonet, J.F., Thierry, G., Cardebat, D.: Renewal of the neurophysiology of language: functional neuroimaging. Physiol. Rev. 85, 49–95 (2005)Google Scholar
  105. 105.
    Indefrey, P., Levelt, W.J.: The spatial and temporal signatures of word production components. Cognition 92, 101–144 (2004)Google Scholar
  106. 106.
    Lazar, R.M., Antoniello, D.: Variability in recovery from aphasia. Curr. Neurol. Neurosci. Rep. 8, 497–502 (2008)Google Scholar
  107. 107.
    Dronkers, N.F., Wilkins, D.P., Van Jr., V.R., et al.: Lesion analysis of the brain areas involved in language comprehension. Cognition 92, 145–177 (2004)Google Scholar
  108. 108.
    Demonet, J.F., Chollet, F., Ramsay, S., et al.: The anatomy of phonological and semantic processing in normal subjects. Brain 115(pt 6), 1753–1768 (1992)Google Scholar
  109. 109.
    McKiernan, K.A., D’Angelo, B.R., Kaufman, J.N., et al.: Interrupting the “stream of consciousness”: an fMRI investigation. Neuroimage 29, 1185–1191 (2006)Google Scholar
  110. 110.
    Stark, C.E., Squire, L.R.: When zero is not zero: the problem of ambiguous baseline conditions in fMRI. Proc. Natl. Acad. Sci. U.S.A. 98, 12760–12766 (2001)ADSGoogle Scholar
  111. 111.
    FitzGerald, D.B., Cosgrove, G.R., Ronner, S., et al.: Location of language in the cortex: a comparison between functional MR imaging and electrocortical stimulation. AJNR Am. J. Neuroradiol. 18, 1529–1539 (1997)Google Scholar
  112. 112.
    Pouratian, N., Bookheimer, S.Y., Rex, D.E., et al.: Utility of preoperative functional magnetic resonance imaging for identifying language cortices in patients with vascular malformations. J. Neurosurg. 97, 21–32 (2002)Google Scholar
  113. 113.
    Rutten, G.J., Ramsey, N.F., van Rijen, P.C., et al.: Development of a functional magnetic resonance imaging protocol for intraoperative localization of critical temporoparietal language areas. Ann. Neurol. 51, 350–360 (2002)Google Scholar
  114. 114.
    Roux, F.E., Boulanouar, K., Lotterie, J.A., et al.: Language functional magnetic resonance imaging in preoperative assessment of language areas: correlation with direct cortical stimulation. Neurosurgery 52, 1335–1345 (2003)Google Scholar
  115. 115.
    Wada, J., Rasmussen, T.: Intracarotid injection of sodium amytal for the lateralization of cerebral speech dominance. J. Neurosurg. 17, 262–282 (1960)Google Scholar
  116. 116.
    Meador, K.J., Loring, D.W.: The Wada test: controversies, concerns, and insights. Neurology 52, 1535–1536 (1999)Google Scholar
  117. 117.
    Binder, J.R., Swanson, S.J., Hammeke, T.A., et al.: Determination of language dominance using functional MRI: a comparison with the Wada test. Neurology 46, 978–984 (1996)Google Scholar
  118. 118.
    Lehericy, S., Cohen, L., Bazin, B., et al.: Functional MR evaluation of temporal and frontal language dominance compared with the Wada test. Neurology 54, 1625–1633 (2000)Google Scholar
  119. 119.
    Liegeois, F., Connelly, A., Salmond, C.H., et al.: A direct test for lateralization of language activation using fMRI: comparison with invasive assessments in children with epilepsy. Neuroimage 17, 1861–1867 (2002)Google Scholar
  120. 120.
    Swanson, S.J., Sabsevitz, D.S., Hammeke, T.A., et al.: Functional magnetic resonance imaging of language in epilepsy. Neuropsychol. Rev. 17, 491–504 (2007)Google Scholar
  121. 121.
    Sabsevitz, D.S., Swanson, S.J., Hammeke, T.A., et al.: Use of preoperative functional neuroimaging to predict language deficits from epilepsy surgery. Neurology 60, 1788–1792 (2003)Google Scholar
  122. 122.
    Kubu, C.S., Girvin, J.P., McLachlan, R.S., et al.: Does the intracarotid amobarbital procedure predict global amnesia after temporal lobectomy? Epilepsia 41, 1321–1329 (2000)Google Scholar
  123. 123.
    Simkins-Bullock, J.: Beyond speech lateralization: a review of the variability, reliability, and validity of the intracarotid amobarbital procedure and its nonlanguage uses in epilepsy surgery candidates. Neuropsychol. Rev. 10, 41–74 (2000)Google Scholar
  124. 124.
    Binder, J.R., Sabsevitz, D.S., Swanson, S.J., et al.: Use of preoperative functional MRI to predict verbal memory decline after temporal lobe epilepsy surgery. Epilepsia 49, 1377–1394 (2008)Google Scholar
  125. 125.
    Frings, L., Wagner, K., Halsband, U., et al.: Lateralization of hippocampal activation differs between left and right temporal lobe epilepsy patients and correlates with postsurgical verbal learning decrement. Epilepsy Res. 78, 161–170 (2008)Google Scholar
  126. 126.
    Powell, H.W., Richardson, M.P., Symms, M.R., et al.: Preoperative fMRI predicts memory decline following anterior temporal lobe resection. J. Neurol. Neurosurg. Psychiatry 79, 686–693 (2008)Google Scholar
  127. 127.
    Rabin, M.L., Narayan, V.M., Kimberg, D.Y., et al.: Functional MRI predicts post-surgical memory following temporal lobectomy. Brain 127, 2286–2298 (2004)Google Scholar
  128. 128.
    Constable, R.T., Carpentier, A., Pugh, K., et al.: Investigation of the human hippocampal formation using a randomized event-related paradigm and Z-shimmed functional MRI. Neuroimage 12, 55–62 (2000)Google Scholar
  129. 129.
    Fernandez-Seara, M.A., Wang, J., Wang, Z., et al.: Imaging mesial temporal lobe activation during scene encoding: comparison­ of fMRI using BOLD and arterial spin labeling. Hum. Brain Mapp. 28, 1391–1400 (2007)Google Scholar
  130. 130.
    Binder, J.R., Swanson, S.J., Sabsevitz, D.S., et al.: A comparison of two fMRI methods for predicting verbal memory decline after left temporal lobectomy: language lateralization versus hippocampal activation asymmetry. Epilepsia 51, 618–626 (2010)Google Scholar
  131. 131.
    Fox, M.D., Raichle, M.E.: Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat. Rev. Neurosci. 8, 700–711 (2007)Google Scholar
  132. 132.
    Biswal, B.B., et al.: Toward discovery science of human brain function. Proc. Natl. Acad. Sci. U.S.A. 107, 4734–4739 (2010)ADSGoogle Scholar
  133. 133.
    Biswal, B., Yetkin, F.Z., Haughton, V.M., et al.: Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn. Reson. Med. 34, 537–541 (1995)Google Scholar
  134. 134.
    Cordes, D., Haughton, V.M., Arfanakis, K., et al.: Mapping functionally related regions of brain with functional connectivity MR imaging. AJNR Am. J. Neuroradiol. 21, 1636–1644 (2000)Google Scholar
  135. 135.
    Lowe, M.J., Lurito, J.T., Mathews, V.P., et al.: Quantitative comparison of functional contrast from BOLD-weighted spin-echo and gradient-echo echoplanar imaging at 1.5 Tesla and H2 15O PET in the whole brain. J. Cereb. Blood Flow Metab. 20, 1331–1340 (2000)Google Scholar
  136. 136.
    Fox, M.D., Greicius, M.: Clinical applications of resting state functional connectivity. Front. Syst. Neurosci. 4, 19 (2010)Google Scholar
  137. 137.
    Kokkonen, S.M., Nikkinen, J., Remes, J., et al.: Preoperative localization of the sensorimotor area using independent component analysis of resting-state fMRI. Magn. Reson. Imaging 27, 733–740 (2009)Google Scholar
  138. 138.
    Liu, H., Buckner, R.L., Talukdar, T., et al.: Task-free presurgical mapping using functional magnetic resonance imaging intrinsic activity. J. Neurosurg. 111, 746–754 (2009)Google Scholar
  139. 139.
    Larson-Prior, L.J., Zempel, J.M., Nolan, T.S., et al.: Cortical network functional connectivity in the descent to sleep. Proc. Natl. Acad. Sci. U.S.A. 106, 4489–4494 (2009)ADSGoogle Scholar
  140. 140.
    Vincent, J.L., Patel, G.H., Fox, M.D., et al.: Intrinsic functional architecture in the anaesthetized monkey brain. Nature 447, 83–86 (2007)ADSGoogle Scholar
  141. 141.
    Fujiwara, N., Sakatani, K., Katayama, Y., et al.: Evoked-cerebral blood oxygenation changes in false-negative activations in BOLD contrast functional MRI of patients with brain tumors. Neuroimage 21, 1464–1471 (2004)Google Scholar
  142. 142.
    Schreiber, A., Hubbe, U., Ziyeh, S., et al.: The influence of gliomas and nonglial ­space-occupying lesions on blood-oxygen-level-dependent contrast enhancement. AJNR Am. J. Neuroradiol. 21, 1055–1063 (2000)Google Scholar
  143. 143.
    Hou, B.L., Bradbury, M., Peck, K.K., et al.: Effect of brain tumor neovasculature defined by rCBV on BOLD fMRI activation volume in the ­primary motor cortex. Neuroimage 32, 489–497 (2006)Google Scholar
  144. 144.
    Chen, C.M., Hou, B.L., Holodny, A.I.: Effect of age and tumor grade on BOLD functional MR imaging in preoperative assessment of patients with glioma. Radiology 248, 971–978 (2008)Google Scholar
  145. 145.
    Rauscher, A., Sedlacik, J., Fitzek, C., et al.: High resolution susceptibility weighted MR-imaging of brain tumors during the application of a gaseous agent. Rofo 177, 1065–1069 (2005)Google Scholar
  146. 146.
    Kastrup, A., Li, T.Q., Takahashi, A., et al.: Functional magnetic resonance imaging of regional cerebral blood oxygenation changes during breath holding. Stroke 29, 2641–2645 (1998)Google Scholar
  147. 147.
    Rostrup, E., Larsson, H.B., Toft, P.B., et al.: Functional MRI of CO2 induced increase in cerebral perfusion. NMR Biomed. 7, 29–34 (1994)Google Scholar
  148. 148.
    Li, T.Q., Kastrup, A., Takahashi, A.M., et al.: Functional MRI of human brain during breath holding by BOLD and FAIR techniques. Neuroimage 9, 243–249 (1999)Google Scholar
  149. 149.
    Robinson, S.P., Rijken, P.F., Howe, F.A., et al.: Tumor vascular architecture and function evaluated by non-invasive susceptibility MRI methods and immunohistochemistry. J. Magn. Reson. Imaging 17, 445–454 (2003)Google Scholar
  150. 150.
    Stillman, A.E., Hu, X., Jerosch-Herold, M.: Functional MRI of brain during breath holding at 4 T. Magn. Reson. Imaging 13, 893–897 (1995)Google Scholar
  151. 151.
    Taylor, N.J., Baddeley, H., Goodchild, K.A., et al.: BOLD MRI of human tumor oxygenation during carbogen breathing. J. Magn. Reson. Imaging 14, 156–163 (2001)Google Scholar
  152. 152.
    Vigue, B., Ract, C., Zlotine, N., et al.: Relationship between intracranial pressure, mild hypothermia and temperature-corrected PaCO2 in patients with traumatic brain injury. Intensive Care Med. 26, 722–728 (2000)Google Scholar
  153. 153.
    Liu, H.L., Huang, J.C., Wu, C.T., et al.: Detectability of blood oxygenation level-dependent signal changes during short breath hold duration. Magn. Reson. Imaging 20, 643–648 (2002)Google Scholar
  154. 154.
    Hsu, Y.Y., Chang, C.N., Jung, S.M., et al.: Blood oxygenation level-dependent MRI of cerebral gliomas during breath holding. J. Magn. Reson. Imaging 19, 160–167 (2004)Google Scholar
  155. 155.
    Hendler, T., Pianka, P., Sigal, M., et al.: Delineating gray and white matter involvement in brain lesions: three-dimensional alignment of functional magnetic resonance and diffusion-tensor imaging. J. Neurosurg. 99, 1018–1027 (2003)Google Scholar
  156. 156.
    Parmar, H., Sitoh, Y.Y., Yeo, T.T.: Combined magnetic resonance tractography and functional magnetic resonance imaging in evaluation of brain tumors involving the motor system. J. Comput. Assist. Tomogr. 28, 551–556 (2004)Google Scholar
  157. 157.
    Schonberg, T., Pianka, P., Hendler, T., et al.: Characterization of displaced white matter by brain tumors using combined DTI and fMRI. Neuroimage 30, 1100–1111 (2006)Google Scholar
  158. 158.
    Ulmer, J.L., Salvan, C.V., Mueller, W.M., et al.: The role of diffusion tensor imaging in establishing the proximity of tumor borders to functional brain systems: implications for preoperative risk assessments and postoperative outcomes. Technol. Cancer Res. Treat. 3, 567–576 (2004)Google Scholar
  159. 159.
    Cruz Jr., L.C., Sorensen, A.G.: Diffusion tensor magnetic resonance imaging of brain tumors. Magn. Reson. Imaging Clin. N. Am. 14, 183–202 (2006)Google Scholar
  160. 160.
    Wieshmann, U.C., Symms, M.R., Parker, G.J., et al.: Diffusion tensor imaging demonstrates deviation of fibres in normal appearing white matter adjacent to a brain tumour. J. Neurol. Neurosurg. Psychiatry 68, 501–503 (2000)Google Scholar
  161. 161.
    Witwer, B.P., Moftakhar, R., Hasan, K.M., et al.: Diffusion-tensor imaging of white matter tracts in patients with cerebral neoplasm. J. Neurosurg. 97, 568–575 (2002)Google Scholar
  162. 162.
    Jellison, B.J., Field, A.S., Medow, J., et al.: Diffusion tensor imaging of cerebral white matter: a pictorial review of physics, fiber tract anatomy, and tumor imaging patterns. AJNR Am. J. Neuroradiol. 25, 356–369 (2004)Google Scholar
  163. 163.
    Guye, M., Parker, G.J., Symms, M., et al.: Combined functional MRI and tractography to demonstrate the connectivity of the human primary motor cortex in vivo. Neuroimage 19, 1349–1360 (2003)Google Scholar
  164. 164.
    Assaf, Y., Pasternak, O.: Diffusion tensor imaging (DTI)-based white matter mapping in brain research: a review. J. Mol. Neurosci. 34, 51–61 (2008)Google Scholar
  165. 165.
    Kleiser, R., Staempfli, P., Valavanis, A., et al.: Impact of fMRI-guided advanced DTI fiber tracking techniques on their clinical applications in patients with brain tumors. Neuroradiology 52, 37–46 (2010)Google Scholar
  166. 166.
    Pasternak, O., Sochen, N., Gur, Y., et al.: Free water elimination and ­mapping from diffusion MRI. Magn. Reson. Med. 62, 717–730 (2009)Google Scholar
  167. 167.
    Chen, X., Weigel, D., Ganslandt, O., et al.: Prediction of visual field deficits by diffusion tensor imaging in temporal lobe epilepsy surgery. Neuroimage 45, 286–297 (2009)Google Scholar
  168. 168.
    Taoka, T., Sakamoto, M., Nakagawa, H., et al.: Diffusion tensor tractography of the Meyer loop in cases of temporal lobe resection for temporal lobe epilepsy: correlation between postsurgical visual field defect and anterior limit of Meyer loop on tractography. AJNR Am. J. Neuroradiol. 29, 1329–1334 (2008)Google Scholar
  169. 169.
    Smith, S.J.: EEG in the diagnosis, classification, and management of patients with epilepsy. J. Neurol. Neurosurg. Psychiatry 76(suppl 2), ii2–ii7 (2005)Google Scholar
  170. 170.
    Benbadis, S.R., Tatum, W.O.: Overintepretation of EEGs and misdiagnosis of epilepsy. J. Clin. Neurophysiol. 20, 42–44 (2003)Google Scholar
  171. 171.
    Knake, S., et al.: The value of multichannel MEG and EEG in the presurgical evaluation of 70 epilepsy patients. Epilepsy Res. 69, 80–86 (2006)Google Scholar
  172. 172.
    Stufflebeam, S.M., Tanaka, N., Ahlfors, S.P.: Clinical applications of magnetoencephalography. Hum. Brain Mapp. 30, 1813–1823 (2009)Google Scholar
  173. 173.
    Ramantani, G., Boor, R., Paetau, R., et al.: MEG versus EEG: influence of background activity on interictal spike detection. J. Clin. Neurophysiol. 23, 498–508 (2006)Google Scholar
  174. 174.
    de Jongh, A., de Munck, J.C., Goncalves, S.I., et al.: Differences in MEG/EEG epileptic spike yields explained by regional differences in signal-to-noise ratios. J. Clin. Neurophysiol. 22, 153–158 (2005)Google Scholar
  175. 175.
    Barkley, G.L., Baumgartner, C.: MEG and EEG in epilepsy. J. Clin. Neurophysiol. 20, 163–178 (2003)Google Scholar
  176. 176.
    Gotman, J., Benar, C.G., Dubeau, F.: Combining EEG and FMRI in epilepsy: methodological challenges and clinical results. J. Clin. Neurophysiol. 21, 229–240 (2004)Google Scholar
  177. 177.
    Grova, C., Daunizeau, J., Kobayashi, E., et al.: Concordance between distributed EEG source localization and simultaneous EEG-fMRI studies of epileptic spikes. Neuroimage 39, 755–774 (2008)Google Scholar
  178. 178.
    Salek-Haddadi, A., Diehl, B., Hamandi, K., et al.: Hemodynamic correlates of epileptiform discharges: an EEG-fMRI study of 63 patients with focal epilepsy. Brain Res. 1088, 148–166 (2006)Google Scholar
  179. 179.
    Groening, K., Brodbeck, V., Moeller, F., et al.: Combination of EEG-fMRI and EEG source analysis improves interpretation of spike-associated activation networks in paediatric pharmacoresistant focal epilepsies. Neuroimage 46, 827–833 (2009)Google Scholar
  180. 180.
    Vulliemoz, S., Thornton, R., Rodionov, R., et al.: The spatio-temporal mapping of epileptic networks: combination of EEG-fMRI and EEG source imaging. Neuroimage 46, 834–843 (2009)Google Scholar
  181. 181.
    Zijlmans, M., Huiskamp, G., Hersevoort, M., et al.: EEG-fMRI in the preoperative work-up for epilepsy surgery. Brain 130, 2343–2353 (2007)Google Scholar
  182. 182.
    Agirre-Arrizubieta, Z., Huiskamp, G.J., Ferrier, C.H., et al.: Interictal magnetoencephalography and the irritative zone in the electrocorticogram. Brain 132, 3060–3071 (2009)Google Scholar
  183. 183.
    Shigeto, H., Morioka, T., Hisada, K., et al.: Feasibility and limitations of magnetoencephalographic detection of epileptic discharges: simultaneous recording of magnetic fields and electrocorticography. Neurol. Res. 24, 531–536 (2002)Google Scholar

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© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.NeuroscienceUniversity of ManitobaWinnipegCanada
  2. 2.NeurologyMedical College of WisconsinMilwaukeeUSA

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