Brain Imaging in Behavioral Medicine and Clinical Neuroscience: Synthesis

  • Ronald A. Cohen
  • Lawrence H. Sweet


It has been less than two decades since Ogawa, Kwong, and other neuroimaging pioneers published the first studies demonstrating that blood oxygen level-dependent (BOLD) changes could be detected using magnetic resonance (MR)-based methods (Kwong et al., Proc Natl Acad Sci USA 89:5675–5679, 1992; Ogawa et al., Proc Natl Acad Sci USA 89:5951–5955, 1992; Ogawa et al., Proc Natl Acad Sci USA 87(24):9868–9872, 1990; Ogawa et al., Magn Reson Med 14(1):68–78, 1990). These results rapidly spurred functional magnetic resonance imaging (FMRI) investigations of the effects of sensory stimulation, motor function, and basic cognitive processes (Bandettini et al., Hum Brain Mapp 5(2):93–109, 1997; Belliveau et al., Science 254(5032):716–719, 1991; Buckner et al., Neuron 20(2):285–296, 1998; Malach et al., Proc Natl Acad Sci USA 92(18):8135–8139, 1995; Cohen et al., Brain 119 (Pt 1):89–100, 1996; Cramer et al., Hum Brain Mapp 16(4):197–205, 2002; Rao et al., Neuroreport 8(8):1987–1993, 1997) that complemented parallel work that had been emerging a few years before using radiological methods like positron emission tomography (PET) (Petersen et al., Nature 331(6157):585–589, 1988). Since then, there has been an explosion of interest and research in the field of functional brain imaging, along with major methodological advancements. Functional brain imaging has evolved to the point that many universities now have research-dedicated MR scanners independent of the clinical facilities that are often available within affiliated medical center settings. Furthermore, a number of psychology departments have installed MR systems in their on-campus buildings which, given the costs associated with having a dedicated scanner, reflects a growing perception that this technology is likely to have a major impact on cognitive and behavioral science in the years to come.


Positron Emission Tomography Multiple Sclerosis Chronic Fatigue Syndrome Behavioral Medicine Functional Magnetic Resonance Imaging 
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.


  1. 1.
    Kwong KK, Belliveau JW, Chesler DA, et al. Dynamic ­magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci USA. 1992;89:5675–5679.CrossRefPubMedGoogle Scholar
  2. 2.
    Ogawa S, Tank DW, Menon R, et al. Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci USA. 1992;89:5951–5955.CrossRefPubMedGoogle Scholar
  3. 3.
    Ogawa S, Lee TM, Kay AR, Tank DW. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc Natl Acad Sci USA. 1990;87(24):9868–9872.CrossRefPubMedGoogle Scholar
  4. 4.
    Ogawa S, Lee TM, Nayak AS, Glynn P. Oxygenation-sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields. Magn Reson Med. 1990;14(1):68–78.CrossRefPubMedGoogle Scholar
  5. 5.
    Bandettini PA, Kwong KK, Davis TL, et al. Characterization of cerebral blood oxygenation and flow changes during ­prolonged brain activation. Hum Brain Mapp. 1997;5(2):93–109.CrossRefPubMedGoogle Scholar
  6. 6.
    Belliveau JW, Kennedy DN Jr, McKinstry RC, et al. Functional mapping of the human visual cortex by magnetic resonance imaging. Science. 1991;254(5032):716–719.CrossRefPubMedGoogle Scholar
  7. 7.
    Buckner RL, Goodman J, Burock M, et al. Functional-anatomic correlates of object priming in humans revealed by rapid presentation event-related fMRI. Neuron. 1998;20(2): 285–296.CrossRefPubMedGoogle Scholar
  8. 8.
    Malach R, Reppas JB, Benson RR, et al. Object-related activity revealed by functional magnetic resonance imaging in human occipital cortex. Proc Natl Acad Sci USA. 1995;92(18):8135–8139.CrossRefPubMedGoogle Scholar
  9. 9.
    Cohen MS, Kosslyn SM, Breiter HC, et al. Changes in cortical activity during mental rotation. A mapping study using functional MRI. Brain. 1996;119(Pt 1):89–100.CrossRefPubMedGoogle Scholar
  10. 10.
    Cramer SC, Weisskoff RM, Schaechter JD, et al. Motor cortex activation is related to force of squeezing. Hum Brain Mapp. 2002;16(4):197–205.CrossRefPubMedGoogle Scholar
  11. 11.
    Rao SM, Bobholz JA, Hammeke TA, et al. Functional MRI evidence for subcortical participation in conceptual reasoning skills. Neuroreport. 1997;8(8):1987–1993.CrossRefPubMedGoogle Scholar
  12. 12.
    Petersen SE, Fox PT, Posner MI, Mintun M, Raichle ME. Positron emission tomographic studies of the cortical anatomy of single-word processing. Nature. 1988;331(6157): 585–589.CrossRefPubMedGoogle Scholar
  13. 13.
    Ashburner J, Friston KJ. Voxel-based morphometry – the methods. Neuroimage. 2000;11(6 Pt 1):805–821.CrossRefPubMedGoogle Scholar
  14. 14.
    Dale AM, Fischl B, Sereno MI. Cortical surface-based analysis I: segmentation and surface reconstruction. Neuroimage. 1999;9(2):179–194.CrossRefPubMedGoogle Scholar
  15. 15.
    Fischl B, Sereno MI, Dale AM. Cortical surface-based analysis II: inflation, flattening, and a surface-based coordinate system. Neuroimage. 1999;9(2):195–207.CrossRefPubMedGoogle Scholar
  16. 16.
    Fischl B, van der Kouwe A, Destrieux C, et al. Automatically parcellating the human cerebral cortex. Cereb Cortex. 2004;14:11–22.CrossRefPubMedGoogle Scholar
  17. 17.
    Fischl B, Salat DH, Busa E, et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron. 2002;33:341–355.CrossRefPubMedGoogle Scholar
  18. 18.
    Bangen KJ, Restom K, Liu TT, et al. Differential age effects on cerebral blood flow and BOLD response to encoding: associations with cognition and stroke risk. Neurobiol Aging. 2009;30(8):1276–1287.CrossRefPubMedGoogle Scholar
  19. 19.
    Restom K, Bangen KJ, Bondi MW, Perthen JE, Liu TT. Cerebral blood flow and BOLD responses to a memory encoding task: a comparison between healthy young and elderly adults. Neuroimage. 2007;37(2):430–439.CrossRefPubMedGoogle Scholar
  20. 20.
    Hoge RD, Atkinson J, Gill B, Crelier GR, Marrett S, Pike GB. Investigation of BOLD signal dependence on cerebral blood flow and oxygen consumption: the deoxyhemoglobin dilution model. Magn Reson Med. 1999;42(5):849–863.CrossRefPubMedGoogle Scholar
  21. 21.
    Hoge RD, Atkinson J, Gill B, Crelier GR, Marrett S, Pike GB. Linear coupling between cerebral blood flow and oxygen consumption in activated human cortex. Proc Natl Acad Sci USA. 1999;96(16):9403–9408.CrossRefPubMedGoogle Scholar
  22. 22.
    Hoge RD, Atkinson J, Gill B, Crelier GR, Marrett S, Pike GB. Stimulus-dependent BOLD and perfusion dynamics in human V1. Neuroimage. 1999;9(6 Pt 1):573–585.CrossRefPubMedGoogle Scholar
  23. 23.
    Brown GG, Eyler Zorrilla LT, Georgy B, Kindermann SS, Wong EC, Buxton RB. BOLD and perfusion response to finger-thumb apposition after acetazolamide administration: differential relationship to global perfusion. J Cereb Blood Flow Metab. 2003;23(7):829–837.CrossRefPubMedGoogle Scholar
  24. 24.
    Brown GG, Perthen JE, Liu TT, Buxton RB. A primer on functional magnetic resonance imaging. Neuropsychol Rev. 2007;17(2):107–125.CrossRefPubMedGoogle Scholar
  25. 25.
    Guye M, Parker GJ, Symms M, et al. Combined functional MRI and tractography to demonstrate the connectivity of the human primary motor cortex in vivo. Neuroimage. 2003;19(4):1349–1360.CrossRefPubMedGoogle Scholar
  26. 26.
    Mori S, Frederiksen K, van Zijl PC, et al. Brain white matter anatomy of tumor patients evaluated with diffusion tensor imaging. Ann Neurol. 2002;51(3):377–380.CrossRefPubMedGoogle Scholar
  27. 27.
    Inoue T, Ogasawara K, Beppu T, Ogawa A, Kabasawa H. Diffusion tensor imaging for preoperative evaluation of tumor grade in gliomas. Clin Neurol Neurosurg. 2005;107(3): 174–180.CrossRefPubMedGoogle Scholar
  28. 28.
    Laundre BJ, Jellison BJ, Badie B, Alexander AL, Field AS. Diffusion tensor imaging of the corticospinal tract before and after mass resection as correlated with clinical motor findings: preliminary data. AJNR Am J Neuroradiol. 2005;26(4):791–796.PubMedGoogle Scholar
  29. 29.
    Kamada K, Sawamura Y, Takeuchi F, et al. Functional ­identification of the primary motor area by corticospinal tractography. Neurosurgery. 2005;56(1 suppl):98–109. discussion 198–109.CrossRefPubMedGoogle Scholar
  30. 30.
    Nimsky C, Ganslandt O, Hastreiter P, et al. Intraoperative diffusion-tensor MR imaging: shifting of white matter tracts during neurosurgical procedures – initial experience. Radiology. 2005;234(1):218–225.CrossRefPubMedGoogle Scholar
  31. 31.
    Gossl C, Fahrmeir L, Putz B, Auer LM, Auer DP. Fiber tracking from DTI using linear state space models: detectability of the pyramidal tract. Neuroimage. 2002;16(2):378–388.CrossRefPubMedGoogle Scholar
  32. 32.
    Misaki T, Beppu T, Inoue T, Ogasawara K, Ogawa A, Kabasawa H. Use of fractional anisotropy value by diffusion tensor MRI for preoperative diagnosis of astrocytic tumors: case report. J Neurooncol. 2004;70(3):343–348.CrossRefPubMedGoogle Scholar
  33. 33.
    Tropine A, Vucurevic G, Delani P, et al. Contribution of diffusion tensor imaging to delineation of gliomas and glioblastomas. J Magn Reson Imaging. 2004;20(6):905–912.CrossRefPubMedGoogle Scholar
  34. 34.
    Moeller F, Tyvaert L, Nguyen DK, et al. EEG-fMRI: adding to standard evaluations of patients with nonlesional frontal lobe epilepsy. Neurology. 2009;73(23):2023–2030.CrossRefPubMedGoogle Scholar
  35. 35.
    Donaire A, Falcon C, Carreno M, et al. Sequential analysis of fMRI images: A new approach to study human epileptic networks. Epilepsia. 2009;50(12):2526–2537.CrossRefPubMedGoogle Scholar
  36. 36.
    Donaire A, Bargallo N, Falcon C, et al. Identifying the structures involved in seizure generation using sequential analysis of ictal-fMRI data. Neuroimage. 2009;47(1):173–183.CrossRefPubMedGoogle Scholar
  37. 37.
    Auer T, Veto K, Doczi T, et al. Identifying seizure-onset zone and visualizing seizure spread by fMRI: a case report. Epileptic Disord. 2008;10(2):93–100.PubMedGoogle Scholar
  38. 38.
    Jacobs J, Rohr A, Moeller F, et al. Evaluation of epileptogenic networks in children with tuberous sclerosis complex using EEG-fMRI. Epilepsia. 2008;49(5):816–825.CrossRefPubMedGoogle Scholar
  39. 39.
    Ott BR, Heindel WC, Whelihan WM, Caron MD, Piatt AL, Noto RB. A single-photon emission computed tomography imaging study of driving impairment in patients with Alzheimer’s disease. Dement Geriatr Cogn Disord. 2000;11(3): 153–160.CrossRefPubMedGoogle Scholar
  40. 40.
    Bauer M, Langer O, Dal-Bianco P, et al. A positron emission tomography microdosing study with a potential antiamyloid drug in healthy volunteers and patients with Alzheimer’s disease. Clin Pharmacol Ther. 2006;80(3):216–227.CrossRefPubMedGoogle Scholar
  41. 41.
    Small GW, Bookheimer SY, Thompson PM, et al. Current and future uses of neuroimaging for cognitively impaired patients. Lancet Neurol. 2008;7(2):161–172.CrossRefPubMedGoogle Scholar
  42. 42.
    Rowe CC, Ackerman U, Browne W, et al. Imaging of amyloid beta in Alzheimer’s disease with 18F-BAY94-9172, a novel PET tracer: proof of mechanism. Lancet Neurol. 2008;7(2):129–135.CrossRefPubMedGoogle Scholar
  43. 43.
    Jagust W, Reed B, Mungas D, Ellis W, Decarli C. What does fluorodeoxyglucose PET imaging add to a clinical diagnosis of dementia? Neurology. 2007;69(9):871–877.CrossRefPubMedGoogle Scholar
  44. 44.
    McKeith I, O’Brien J, Walker Z, et al. Sensitivity and specificity of dopamine transporter imaging with 123I-FP-CIT SPECT in dementia with Lewy bodies: a phase III, multicentre study. Lancet Neurol. 2007;6(4):305–313.CrossRefPubMedGoogle Scholar
  45. 45.
    Nordberg A. PET imaging of amyloid in Alzheimer’s disease. Lancet Neurol. 2004;3(9):519–527.CrossRefPubMedGoogle Scholar
  46. 46.
    Kemppainen N, Ruottinen H, Nagren K, Rinne JO. PET shows that striatal dopamine D1 and D2 receptors are differentially affected in AD. Neurology. 2000;55(2):205–209.PubMedGoogle Scholar
  47. 47.
    Ishii K, Imamura T, Sasaki M, et al. Regional cerebral glucose metabolism in dementia with Lewy bodies and Alzheimer’s disease. Neurology. 1998;51(1):125–130.PubMedGoogle Scholar
  48. 48.
    Duara R, Grady C, Haxby J, et al. Positron emission tomography in Alzheimer’s disease. Neurology. 1986;36(7): 879–887.PubMedGoogle Scholar
  49. 49.
    Dube AA, Duquette M, Roy M, Lepore F, Duncan G, Rainville P. Brain activity associated with the electrodermal reactivity to acute heat pain. Neuroimage. 2009;45(1): 169–180.CrossRefPubMedGoogle Scholar
  50. 50.
    Burgmer M, Pogatzki-Zahn E, Gaubitz M, Wessoleck E, Heuft G, Pfleiderer B. Altered brain activity during pain processing in fibromyalgia. Neuroimage. 2009;44(2):502–508.CrossRefPubMedGoogle Scholar
  51. 51.
    Kufahl P, Li Z, Risinger R, et al. Expectation modulates human brain responses to acute cocaine: a functional magnetic resonance imaging study. Biol Psychiatry. 2008;63(2):222–230.CrossRefPubMedGoogle Scholar
  52. 52.
    Browndyke JN, Paskavitz J, Sweet LH, et al. Neuroanatomical correlates of malingered memory impairment: event-related fMRI of deception on a recognition memory task. Brain Inj. 2008;22(6):481–489.CrossRefPubMedGoogle Scholar
  53. 53.
    Lee TM, Liu HL, Chan CC, Ng YB, Fox PT, Gao JH. Neural correlates of feigned memory impairment. Neuroimage. 2005;28(2):305–313.CrossRefPubMedGoogle Scholar
  54. 54.
    Reiman EM, Chen K, Liu X, et al. Fibrillar amyloid-beta burden in cognitively normal people at 3 levels of genetic risk for Alzheimer’s disease. Proc Natl Acad Sci USA. 2009;106(16):6820–6825.CrossRefPubMedGoogle Scholar
  55. 55.
    Klunk WE, Lopresti BJ, Ikonomovic MD, et al. Binding of the positron emission tomography tracer Pittsburgh compound-B reflects the amount of amyloid-beta in Alzheimer’s disease brain but not in transgenic mouse brain. J Neurosci. 2005;25(46):10598–10606.CrossRefPubMedGoogle Scholar
  56. 56.
    Klunk WE, Engler H, Nordberg A, et al. Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Ann Neurol. 2004;55(3):306–319.CrossRefPubMedGoogle Scholar
  57. 57.
    Cormode DP, Skajaa T, Fayad ZA, Mulder WJ. Nanotechnology in medical imaging: probe design and applications. Arterioscler Thromb Vasc Biol. 2009;29(7): 992–1000.CrossRefPubMedGoogle Scholar
  58. 58.
    Namdeo M, Saxena S, Tankhiwale R, Bajpai M, Mohan YM, Bajpai SK. Magnetic nanoparticles for drug delivery applications. J Nanosci Nanotechnol. 2008;8(7):3247–3271.CrossRefPubMedGoogle Scholar
  59. 59.
    Sun C, Lee JS, Zhang M. Magnetic nanoparticles in MR imaging and drug delivery. Adv Drug Deliv Rev. 2008;60(11): 1252–1265.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Department of Psychiatry and Human Behaviorthe Institute for Brain Science Warren Alpert Medical School of Brown UniversityProvidenceUSA

Personalised recommendations