Skip to main content

Pitfalls in fMRI

European Radiology volume 19, pages 2689–2706 (2009)Cite this article

Abstract

Several different techniques allow a functional assessment of neuronal activations by magnetic resonance imaging (fMRI). The by far most influential fMRI technique is based on a local T2*-sensitive hemodynamic response to neuronal activation, also known as the blood oxygenation level dependent or BOLD effect. Consequently, the term ‘fMRI’ is often used synonymously with BOLD imaging. Because interpretations of fMRI brain activation maps often appear intuitive and compelling, the reader might be tempted not to critically question the fundamental processes and assumptions. We review some essential processes and assumptions of BOLD fMRI and discuss related confounds and pitfalls in fMRI – from the underlying physiological effect, to data acquisition, data analysis and the interpretation of the results including clinical fMRI. A background framework is provided for the systematic and critical interpretation of fMRI results.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

43,34 €

Price includes VAT (Finland)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Box. 1
Fig. 4
Fig. 5
Fig. 6

Abbreviations

AVM:

arterio-venous malformation

BA:

Brodmann’s Area

BOLD:

blood oxygenation level dependent

CSF:

cerebrospinal fluid

DTI:

diffusion tensor imaging

DW:

diffusion weighted

EEG:

electroencephalography

EPI:

echo-planar imaging

FDR:

false discovery rate

FE:

fixed-effect

fMRI:

functional magnetic resonance imaging

FPR:

false-positive rate

FWER:

family-wise error rate

GE:

gradient echo

GLM:

general linear model

GM:

gray matter

HRF:

hemodynamic response function

ICA:

independent component analysis

MC:

motion correction

ME:

mixed-effect

MEG:

magnetencephalography

MM:

Mixture modeling

NBR:

negative BOLD response

RE:

random effects

ROI:

region of interest

RSN:

resting state networks

SE:

spin echo

SMA:

supplementary motor area

TAL:

Talairach space

TPR:

true-positive rate

VOI:

volume of interest

WM:

white matter

References

  1. Villringer A, Dirnagl U (1995) Coupling of brain activity and cerebral blood flow: basis of functional neuroimaging. Cerebrovasc Brain Metab Rev 3:240–276

    Google Scholar 

  2. Ogawa S, Tank DW, Menon R et al (1992) Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci USA 13:5951–5955

    Google Scholar 

  3. Kwong KK, Belliveau JW, Chesler DA et al (1992) Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci USA 12:5675–5679

    Google Scholar 

  4. Moonen CTW, Bandettini PA, and Aguirre GK (2000) Functional MRI, Springer Verlag, Berlin, Heidelberg, New York

  5. Buxton RB (2002) Introduction to Functional Magnetic Resonance Imaging: Principles and Techniques, Cambridge University Press, Cambridge, UK

  6. Walter H (2005) Funktionelle Bildgebung in Psychiatrie und Psychotherapie: Methodische Grundlagen und klinische Anwendungen, Schattauer

  7. Leon Partain C (2006) JMRI special issue: clinical potential of brain mapping using MRI. J Magn Reson Imaging 6:785–786

    Google Scholar 

  8. Stippich C, Blatow M, and Delmaire C (2007) Clinical Functional MRI: Presurgical Functional Neuroimaging, Medical Radiology/Diagnostic Imaging, Springer Verlag, Berlin, Heidelberg, New York

  9. Rombouts SARB, Barkhof F, and Scheltens P (2008), Clinical Applications of Functional Brain MRI, Oxford University Press, Oxford, UK

  10. Huettel SA, Song AW, and McCarthy G (2008) Functional Magnetic Resonance Imaging, Second edition; Sinauer Associates, Sunderland MA, USA

  11. Logothetis NK (2008) What we can do and what we cannot do with fMRI. Nature 7197:869–878

    Google Scholar 

  12. Logothetis NK, Pauls J, Augath M et al (2001) Neurophysiological investigation of the basis of the fMRI signal. Nature 6843:150–157

    Google Scholar 

  13. Cohen ER, Ugurbil K, Kim SG (2002) Effect of basal conditions on the magnitude and dynamics of the blood oxygenation level-dependent fMRI response. J Cereb Blood Flow Metab 9:1042–1053

    Google Scholar 

  14. Magalhaes AC (2005) Functional magnetic resonance and spectroscopy in drug and substance abuse. Top Magn Reson Imaging 3:247–251

    Google Scholar 

  15. Jacobsen LK, Gore JC, Skudlarski P et al (2002) Impact of intravenous nicotine on BOLD signal response to photic stimulation. Magn Reson Imaging 2:141–145

    Google Scholar 

  16. Seifritz E, Bilecen D, Hanggi D et al (2000) Effect of ethanol on BOLD response to acoustic stimulation: implications for neuropharmacological fMRI. Psychiatry Res 1:1–13

    Google Scholar 

  17. Borgwardt SJ, Allen P, Bhattacharyya S et al (2008) Neural Basis of Delta-9-Tetrahydrocannabinol and Cannabidiol: Effects During Response Inhibition. Biol Psychiatry 11:966–973

    Google Scholar 

  18. Bruhn H, Kleinschmidt A, Boecker H et al (1994) The effect of acetazolamide on regional cerebral blood oxygenation at rest and under stimulation as assessed by MRI. J Cereb Blood Flow Metab 5:742–748

    Google Scholar 

  19. Mulderink TA, Gitelman DR, Mesulam MM et al (2002) On the use of caffeine as a contrast booster for BOLD fMRI studies. Neuroimage 1:37–44

    Google Scholar 

  20. Morton DW, Maravilla KR, Meno JR et al (2002) Systemic theophylline augments the blood oxygen level-dependent response to forepaw stimulation in rats. AJNR Am J Neuroradiol 4:588–593

    Google Scholar 

  21. Chen CM, Hou BL, Holodny AI (2008) Effect of age and tumor grade on BOLD functional MR imaging in preoperative assessment of patients with glioma. Radiology 3:971–978

    Google Scholar 

  22. Carusone LM, Srinivasan J, Gitelman DR et al (2002) Hemodynamic response changes in cerebrovascular disease: implications for functional MR imaging. AJNR Am J Neuroradiol 7:1222–1228

    Google Scholar 

  23. Aguirre GK, Zarahn E, D’esposito M (1998) The variability of human, BOLD hemodynamic responses. Neuroimage 4:360–369

    Google Scholar 

  24. Huettel SA, McCarthy G (2001) Regional differences in the refractory period of the hemodynamic response: an event-related fMRI study. Neuroimage 5:967–976

    Google Scholar 

  25. Saad ZS, Ropella KM, Cox RW et al (2001) Analysis and use of FMRI response delays. Hum Brain Mapp 2:74–93

    Google Scholar 

  26. Haller S, Wetzel SG, Radue EW et al (2006) Mapping continuous neuronal activation without an ON-OFF paradigm: initial results of BOLD ceiling fMRI. Eur J Neurosci 9:2672–2678

    Google Scholar 

  27. Haller S, Bonati LH, Rick J et al (2008) Reduced Cerebrovascular Reserve at CO2 BOLD MR Imaging Is Associated with Increased Risk of Periinterventional Ischemic Lesions during Carotid Endarterectomy or Stent Placement: Preliminary Results. Radiology 1:251–258

    Google Scholar 

  28. Rostrup E, Law I, Blinkenberg M et al (2000) Regional differences in the CBF and BOLD responses to hypercapnia: a combined PET and fMRI study. Neuroimage 2:87–97

    Google Scholar 

  29. Preibisch C, Haase A (2001) Perfusion imaging using spin-labeling methods: contrast-to-noise comparison in functional MRI applications. Magn Reson Med 1:172–182

    Google Scholar 

  30. Helenius J, Perkio J, Soinne L et al (2003) Cerebral hemodynamics in a healthy population measured by dynamic susceptibility contrast MR imaging. Acta Radiol 5:538–546

    Google Scholar 

  31. Wise RG, Ide K, Poulin MJ et al (2004) Resting fluctuations in arterial carbon dioxide induce significant low frequency variations in BOLD signal. Neuroimage 4:1652–1664

    Google Scholar 

  32. van der Zande FH, Hofman PA, Backes WH (2005) Mapping hypercapnia-induced cerebrovascular reactivity using BOLD MRI. Neuroradiology 2:114–120

    Google Scholar 

  33. D’Arcy RC, Hamilton A, Jarmasz M et al (2006) Exploratory data analysis reveals visuovisual interhemispheric transfer in functional magnetic resonance imaging. Magn Reson Med 4:952–958

    Google Scholar 

  34. Mazerolle EL, D’Arcy RC, and Beyea SD (2008) Detecting functional magnetic resonance imaging activation in white matter: interhemispheric transfer across the corpus callosum. BMC Neurosci 9:84

    Google Scholar 

  35. Corbetta M, Miezin FM, Dobmeyer S et al (1990) Attentional modulation of neural processing of shape, color, and velocity in humans. Science 4962:1556–1559

    Google Scholar 

  36. Braitenberg V, Schuez A (1998) Cortex: Statistics and Geometry of Neuronal Connectivity, 2nd edn. Springer, Berlin

    Google Scholar 

  37. Jueptner M, Weiller C (1995) Review: does measurement of regional cerebral blood flow reflect synaptic activity. Implications for PET and fMRI. Neuroimage 2:148–156

    CAS  Google Scholar 

  38. Stefanovic B, Warnking JM, Pike GB (2004) Hemodynamic and metabolic responses to neuronal inhibition. Neuroimage 2:771–778

    Google Scholar 

  39. Shmuel A, Yacoub E, Pfeuffer J et al (2002) Sustained negative BOLD, blood flow and oxygen consumption response and its coupling to the positive response in the human brain. Neuron 6:1195–1210

    Google Scholar 

  40. Shmuel A, Augath M, Oeltermann A et al (2006) Negative functional MRI response correlates with decreases in neuronal activity in monkey visual area V1. Nat Neurosci 4:569–577

    Google Scholar 

  41. Uludag K, Dubowitz DJ, Yoder EJ et al (2004) Coupling of cerebral blood flow and oxygen consumption during physiological activation and deactivation measured with fMRI. Neuroimage 1:148–155

    Google Scholar 

  42. Friston KJ, Price CJ, Fletcher P et al (1996) The trouble with cognitive subtraction. Neuroimage 2:97–104

    Google Scholar 

  43. Binder JR, Swanson SJ, Hammeke TA et al (2008) A comparison of five fMRI protocols for mapping speech comprehension systems. Epilepsia 12:1980–1997

    Google Scholar 

  44. Amaro EJ, Barker GJ (2006) Study design in fMRI: basic principles. Brain Cogn 3:220–232

    Google Scholar 

  45. Cunnington R, Windischberger C, Deecke L et al (2002) The preparation and execution of self-initiated and externally-triggered movement: a study of event-related fMRI. Neuroimage 2:373–385

    Google Scholar 

  46. Buckner RL, Bandettini PA, O’Craven KM et al (1996) Detection of cortical activation during averaged single trials of a cognitive task using functional magnetic resonance imaging. Proc Natl Acad Sci USA 25:14878–14883

    Google Scholar 

  47. Friston KJ, Fletcher P, Josephs O et al (1998) Event-related fMRI: characterizing differential responses. Neuroimage 1:30–40

    Google Scholar 

  48. Burock MA, Buckner RL, Woldorff MG et al (1998) Randomized event-related experimental designs allow for extremely rapid presentation rates using functional MRI. Neuroreport 16:3735–3739

    Google Scholar 

  49. Biswal B, Yetkin FZ, Haughton VM et al (1995) Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 4:537–541

    Google Scholar 

  50. Damoiseaux JS, Rombouts SA, Barkhof F et al (2006) Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci USA 37:13848–13853

    Google Scholar 

  51. Sorg C, Riedl V, Muhlau M et al (2007) Selective changes of resting-state networks in individuals at risk for Alzheimer’s disease. Proc Natl Acad Sci USA 47:18760–18765

    Google Scholar 

  52. Hajnal JV, Myers R, Oatridge A et al (1994) Artifacts due to stimulus correlated motion in functional imaging of the brain. Magn Reson Med 3:283–291

    Google Scholar 

  53. Smith SM, Jenkinson M, Woolrich MW et al (2004) Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23 Suppl 1:S208–19

    Google Scholar 

  54. Soltysik DA, Hyde JS (2006) Strategies for block-design fMRI experiments during task-related motion of structures of the oral cavity. Neuroimage 4:1260–1271

    Google Scholar 

  55. Heim S, Amunts K, Mohlberg H et al (2006) Head motion during overt language production in functional magnetic resonance imaging. Neuroreport 6:579–582

    Google Scholar 

  56. Edward V, Windischberger C, Cunnington R et al (2000) Quantification of fMRI artifact reduction by a novel plaster cast head holder. Hum Brain Mapp 3:207–213

    Google Scholar 

  57. Bandettini PA, Wong EC, Hinks RS et al (1992) Time course EPI of human brain function during task activation. Magn Reson Med 2:390–397

    Google Scholar 

  58. Ogawa S, Menon RS, Tank DW et al (1993) Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model. Biophys J 3:803–812

    Google Scholar 

  59. Thulborn KR, Chang SY, Shen GX et al (1997) High-resolution echo-planar fMRI of human visual cortex at 3.0 tesla. NMR Biomed 4–5:183–190

    Google Scholar 

  60. Wegner C, Filippi M, Korteweg T et al (2008) Relating functional changes during hand movement to clinical parameters in patients with multiple sclerosis in a multi-centre fMRI study. Eur J Neurol 2:113–122

    Google Scholar 

  61. Schulte AC, Speck O, Oesterle C et al (2001) Separation and quantification of perfusion and BOLD effects by simultaneous acquisition of functional I(0)- and T2(*)-parameter maps. Magn Reson Med 5:811–816

    Google Scholar 

  62. Schmitz BL, Aschoff AJ, Hoffmann MH et al (2005) Advantages and pitfalls in 3T MR brain imaging: a pictorial review. AJNR Am J Neuroradiol 9:2229–2237

    Google Scholar 

  63. Duong TQ, Yacoub E, Adriany G et al (2003) Microvascular BOLD contribution at 4 and 7 T in the human brain: gradient-echo and spin-echo fMRI with suppression of blood effects. Magn Reson Med 6:1019–1027

    Google Scholar 

  64. Karakas S, Kavakli A (2005) Morphometric examination of the paranasal sinuses and mastoid air cells using computed tomography. Ann Saudi Med 1:41–45

    Google Scholar 

  65. Blaimer M, Breuer F, Mueller M et al (2004) SMASH, SENSE, PILS, GRAPPA: how to choose the optimal method. Top Magn Reson Imaging 4:223–236

    Google Scholar 

  66. Dietrich O, Raya JG, Reeder SB et al (2008) Influence of multichannel combination, parallel imaging and other reconstruction techniques on MRI noise characteristics. Magn Reson Imaging 6:754–762

    Google Scholar 

  67. Dietrich O, Raya JG, Reeder SB et al (2007) Measurement of signal-to-noise ratios in MR images: influence of multichannel coils, parallel imaging, and reconstruction filters. J Magn Reson Imaging 2:375–385

    Google Scholar 

  68. Bandettini PA, Jesmanowicz A, Van Kylen J et al (1998) Functional MRI of brain activation induced by scanner acoustic noise. Magn Reson Med 3:410–416

    Google Scholar 

  69. Hall DA, Haggard MP, Akeroyd MA et al (1999) “Sparse” temporal sampling in auditory fMRI. Hum Brain Mapp 3:213–223

    Google Scholar 

  70. Seifritz E, Di Salle F, Esposito F et al (2006) Enhancing BOLD response in the auditory system by neurophysiologically tuned fMRI sequence. Neuroimage 3:1013–1022

    Google Scholar 

  71. Giraud AL, Lorenzi C, Ashburner J et al (2000) Representation of the temporal envelope of sounds in the human brain. J Neurophysiol 3:1588–1598

    Google Scholar 

  72. Fox PT, Raichle ME (1984) Stimulus rate dependence of regional cerebral blood flow in human striate cortex, demonstrated by positron emission tomography. J Neurophysiol 5:1109–1120

    Google Scholar 

  73. Banbury SP, Macken WJ, Tremblay S et al (2001) Auditory distraction and short-term memory: phenomena and practical implications. Hum Factors 1:12–29

    Google Scholar 

  74. Mazard A, Mazoyer B, Etard O et al (2002) Impact of fMRI acoustic noise on the functional anatomy of visual mental imagery. J Cogn Neurosci 2:172–186

    Google Scholar 

  75. Novitski N, Anourova I, Martinkauppi S et al (2003) Effects of noise from functional magnetic resonance imaging on auditory event-related potentials in working memory task. Neuroimage 2:1320–1328

    Google Scholar 

  76. Tomasi D, Caparelli EC, Chang L et al (2005) fMRI-acoustic noise alters brain activation during working memory tasks. Neuroimage 2:377–386

    Google Scholar 

  77. Haller S, Bartsch AJ, Radue EW et al (2005) Effect of fMRI acoustic noise on non-auditory working memory task: comparison between continuous and pulsed sound emitting EPI. MAGMA 5:263–271

    Google Scholar 

  78. Bartsch AJ and Specht K (2003) Detection of the scanner’s genuine gradient noise by functional echo planar imaging. Riv Neuroradiol 16:995–1000

    Google Scholar 

  79. Seifritz E, Esposito F, Hennel F et al (2002) Spatiotemporal pattern of neural processing in the human auditory cortex. Science 5587:1706–1708

    Google Scholar 

  80. Bartsch AJ, Homola G, Thesen S et al (2007) Scanning for the scanner: FMRI of audition by read-out omissions from echo-planar imaging. Neuroimage 1:234–243

    Google Scholar 

  81. Smith SM, Nichols TE (2009) Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage 1:83–98

    Google Scholar 

  82. Friston KJ, Holmes AP, Worsley KJ et al (1995) Statistical Parametric Maps in Functional Imaging: A General Linear Approach. Hum Brain Mapp 2:189–210

    Google Scholar 

  83. Beckmann CF, Smith SM (2004) Probabilistic independent component analysis for functional magnetic resonance imaging. IEEE Trans Med Imaging 2:137–152

    Google Scholar 

  84. Beckmann CF, Smith SM (2005) Tensorial extensions of independent component analysis for multisubject FMRI analysis. Neuroimage 1:294–311

    Google Scholar 

  85. Calhoun VD, Adali T, Pearlson GD et al (2001) A method for making group inferences from functional MRI data using independent component analysis. Hum Brain Mapp 3:140–151

    Google Scholar 

  86. Guo Y, Pagnoni G (2008) A unified framework for group independent component analysis for multi-subject fMRI data. Neuroimage 3:1078–1093

    Google Scholar 

  87. Logan BR, Rowe DB (2004) An evaluation of thresholding techniques in fMRI analysis. Neuroimage 1:95–108

    Google Scholar 

  88. Woolrich MW, Ripley BD, Brady M et al (2001) Temporal autocorrelation in univariate linear modeling of FMRI data. Neuroimage 6:1370–1386

    Google Scholar 

  89. Friston KJ, Worsley KJ, Frackowiak RSJ et al (1994) Assessing the Significance of Focal Activations Using their Spatial Extent. Hum Brain Mapp 1:214–220

    Google Scholar 

  90. Worsley KJ (2005) An improved theoretical P value for SPMs based on discrete local maxima. Neuroimage 4:1056–1062

    Google Scholar 

  91. Genovese CR, Lazar NA, Nichols T (2002) Thresholding of statistical maps in functional neuroimaging using the false discovery rate. Neuroimage 4:870–878

    Google Scholar 

  92. Hartvig NV, Jensen JL (2000) Spatial mixture modeling of fMRI data. Hum Brain Mapp 4:233–248

    Google Scholar 

  93. Beckmann CF, Woolrich MW, Smith SM (2003) Gaussian/Gamma mixture modelling of ICA/GLM spatial maps. Ninth International Conference on Functional Mapping of the Human Brain 2:S985

    Google Scholar 

  94. Woolrich MW, Behrens TE, Beckmann CF et al (2005) Mixture models with adaptive spatial regularization for segmentation with an application to FMRI data. IEEE Trans Med Imaging 1:1–11

    Google Scholar 

  95. Bartsch AJ, Homola G, Biller A et al (2006) Diagnostic functional MRI: illustrated clinical applications and decision-making. J Magn Reson Imaging 6:921–932

    Google Scholar 

  96. Friston KJ, Holmes AP, Price CJ et al (1999) Multisubject fMRI studies and conjunction analyses. Neuroimage 4:385–396

    Google Scholar 

  97. Beckmann CF, Jenkinson M, Smith SM (2003) General multilevel linear modeling for group analysis in FMRI. Neuroimage 2:1052–1063

    Google Scholar 

  98. Woolrich MW, Behrens TE, Beckmann CF et al (2004) Multilevel linear modelling for FMRI group analysis using Bayesian inference. Neuroimage 4:1732–1747

    Google Scholar 

  99. Friston KJ, Holmes AP, Worsley KJ (1999) How many subjects constitute a study. Neuroimage 1:1–5

    Google Scholar 

  100. Price CJ, Friston KJ (1997) Cognitive conjunction: a new approach to brain activation experiments. Neuroimage 4 Pt 1:261–270

    Google Scholar 

  101. Nichols T, Brett M, Andersson J et al (2005) Valid conjunction inference with the minimum statistic. Neuroimage 3:653–660

    Google Scholar 

  102. Seghier ML (2008) Laterality index in functional MRI: methodological issues. Magn Reson Imaging 5:594–601

    Google Scholar 

  103. Richter W, Ugurbil K, Georgopoulos A et al (1997) Time-resolved fMRI of mental rotation. Neuroreport 17:3697–3702

    Article  Google Scholar 

  104. Menon RS, Luknowsky DC, Gati JS (1998) Mental chronometry using latency-resolved functional MRI. Proc Natl Acad Sci USA 18:10902–10907

    Google Scholar 

  105. Formisano E, Linden DE, Di Salle F et al (2002) Tracking the mind’s image in the brain I: time-resolved fMRI during visuospatial mental imagery. Neuron 1:185–194

    Google Scholar 

  106. Hernandez L, Badre D, Noll D et al (2002) Temporal sensitivity of event-related fMRI. Neuroimage 2:1018–1026

    Google Scholar 

  107. Bellgowan PS, Saad ZS, Bandettini PA (2003) Understanding neural system dynamics through task modulation and measurement of functional MRI amplitude, latency, and width. Proc Natl Acad Sci USA 3:1415–1419

    Google Scholar 

  108. Haller S, Klarhoefer M, Schwarzbach J et al (2007) Spatial and temporal analysis of fMRI data on word and sentence reading. Eur J Neurosci 7:2074–2084

    Google Scholar 

  109. Woolrich MW, Jenkinson M, Brady JM et al (2004) Fully Bayesian spatio-temporal modeling of FMRI data. IEEE Trans Med Imaging 2:213–231

    Google Scholar 

  110. Woolrich MW, Behrens TE, Smith SM (2004) Constrained linear basis sets for HRF modelling using Variational Bayes. Neuroimage 4:1748–1761

    Google Scholar 

  111. Broca P (1861) Remarques sur le siège de la faculté de langage articulé, suives d’une observation d’aphémie (perte de la parole). Bulletin de la Societe de Anatomie 36:330–357

    Google Scholar 

  112. Hamzei F, Rijntjes M, Dettmers C et al (2003) The human action recognition system and its relationship to Broca’s area: an fMRI study. Neuroimage 3:637–644

    Google Scholar 

  113. Hagoort P (2005) On Broca, brain, and binding: a new framework. Trends Cogn Sci 9:416–423

    PubMed  Google Scholar 

  114. Mesulam MM (1998) From sensation to cognition. Brain Pt 6:1013–1052

    Google Scholar 

  115. Haxby JV, Gobbini MI, Furey ML et al (2001) Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science 5539:2425–2430

    Google Scholar 

  116. Bogomolny DL, Petrovich NM, Hou BL et al (2004) Functional MRI in the Brain Tumor Patient. Topics in Magnetic Resonance Imaging 5:325

    Google Scholar 

  117. Sunaert S (2006) Presurgical planning for tumor resectioning. J Magn Reson Imaging 6:887–905

    Google Scholar 

  118. Sperling R (2007) Functional MRI studies of associative encoding in normal aging, mild cognitive impairment, and Alzheimer’s disease. Ann NY Acad Sci 1097:146–155

    Google Scholar 

  119. Fusar-Poli P, Perez J, Broome M et al (2007) Neurofunctional correlates of vulnerability to psychosis: a systematic review and meta-analysis. Neurosci Biobehav Rev 4:465–484

    Google Scholar 

  120. Hsu YY, Chang CN, Jung SM et al (2004) Blood oxygenation level-dependent MRI of cerebral gliomas during breath holding. J Magn Reson Imaging 2:160–167

    Google Scholar 

  121. Fujiwara N, Sakatani K, Katayama Y et al (2004) Evoked-cerebral blood oxygenation changes in false-negative activations in BOLD contrast functional MRI of patients with brain tumors. Neuroimage 4:1464–1471

    Google Scholar 

  122. Kim MJ, Holodny AI, Hou BL et al (2005) The effect of prior surgery on blood oxygen level-dependent functional MR imaging in the preoperative assessment of brain tumors. AJNR Am J Neuroradiol 8:1980–1985

    Google Scholar 

  123. Vlieger EJ, Majoie CB, Leenstra S et al (2004) Functional magnetic resonance imaging for neurosurgical planning in neurooncology. Eur Radiol 7:1143–1153

    Google Scholar 

  124. Yousry TA, Schmid UD, Alkadhi H et al (1997) Localization of the motor hand area to a knob on the precentral gyrus. A new landmark. Brain Pt 1:141–157

    Google Scholar 

  125. Gordon AM, Lee JH, Flament D et al (1998) Functional magnetic resonance imaging of motor, sensory, and posterior parietal cortical areas during performance of sequential typing movements. Exp Brain Res 2:153–166

    Google Scholar 

  126. Chung GH, Han YM, Jeong SH et al (2005) Functional heterogeneity of the supplementary motor area. AJNR Am J Neuroradiol 7:1819–1823

    Google Scholar 

  127. Nielsen F (2003) The Brede database: a small database for functional neuroimaging. 9th International Conference on Functional Mapping of the Human Brain 2:Available on CD-Rom.

  128. Cabeza R, Nyberg L (2000) Imaging cognition II: An empirical review of 275 PET and fMRI studies. J Cogn Neurosci 1:1–47

    Google Scholar 

  129. Bookheimer S (2007) Pre-surgical language mapping with functional magnetic resonance imaging. Neuropsychol Rev 2:145–155

    Google Scholar 

  130. Knecht S, Drager B, Deppe M et al (2000) Handedness and hemispheric language dominance in healthy humans. Brain 123:2512–2518

    Google Scholar 

  131. Jorgens S, Kleiser R, Indefrey P et al (2007) Handedness and functional MRI-activation patterns in sentence processing. Neuroreport 13:1339–1343

    Google Scholar 

  132. Adcock JE, Wise RG, Oxbury JM et al (2003) Quantitative fMRI assessment of the differences in lateralization of language-related brain activation in patients with temporal lobe epilepsy. Neuroimage 2:423–438

    Google Scholar 

  133. Perani D, Abutalebi J, Paulesu E et al (2003) The role of age of acquisition and language usage in early, high-proficient bilinguals: an fMRI study during verbal fluency. Hum Brain Mapp 3:170–182

    Google Scholar 

  134. Perani D, Paulesu E, Galles NS et al (1998) The bilingual brain. Proficiency and age of acquisition of the second language. Brain Pt 10:1841–1852

    Google Scholar 

  135. Bloch C, Kaiser A, Kuenzli E et al (2009) The age of second language acquisition determines the variability in activation elicited by narration in three languages in Broca’s and Wernicke’s area. Neuropsychologia 47(3):625–33

    PubMed  Google Scholar 

  136. Woermann FG, Jokeit H, Luerding R et al (2003) Language lateralization by Wada test and fMRI in 100 patients with epilepsy. Neurology 5:699–701

    Google Scholar 

  137. Roberts DW, Hartov A, Kennedy FE et al (1998) Intraoperative brain shift and deformation: a quantitative analysis of cortical displacement in 28 cases. Neurosurgery 4:749–58 discussion 758–60

    Google Scholar 

  138. Nimsky C, Ganslandt O, Cerny S et al (2000) Quantification of, Visualization of, and Compensation for Brain Shift Using Intraoperative Magnetic Resonance Imaging. Neurosurgery 5:1070

    Google Scholar 

  139. Kyriacou SK, Mohamed A, Miller K et al (2002) Brain mechanics For neurosurgery: modeling issues. Biomech Model Mechanobiol 2:151–164

    Google Scholar 

  140. Gasser T, Ganslandt O, Sandalcioglu E et al (2005) Intraoperative functional MRI: implementation and preliminary experience. Neuroimage 3:685–693

    Google Scholar 

  141. Roessler K, Donat M, Lanzenberger R et al (2005) Evaluation of preoperative high magnetic field motor functional MRI (3 Tesla) in glioma patients by navigated electrocortical stimulation and postoperative outcome. J Neurol Neurosurg Psychiatry 8:1152–1157

    Google Scholar 

  142. Haberg A, Kvistad KA, Unsgard G et al (2004) Preoperative blood oxygen level-dependent functional magnetic resonance imaging in patients with primary brain tumors: clinical application and outcome. Neurosurgery 4:902–14 discussion 914–5

    Google Scholar 

  143. Basser PJ (1997) New histological and physiological stains derived from diffusion-tensor MR images. Ann NY Acad Sci 820:123–138

    Google Scholar 

  144. Smits M, Vernooij MW, Wielopolski PA et al (2007) Incorporating functional MR imaging into diffusion tensor tractography in the preoperative assessment of the corticospinal tract in patients with brain tumors. AJNR Am J Neuroradiol 7:1354–1361

    Google Scholar 

  145. Kamada K, Todo T, Masutani Y et al (2007) Visualization of the frontotemporal language fibers by tractography combined with functional magnetic resonance imaging and magnetoencephalography. J Neurosurg 1:90–98

    Google Scholar 

  146. Bartsch AJ, Biller A, Homola G (2008) ‘Tractography for surgical targeting’. in: Johansen-Berg H and TE Behrens (Eds.), Imaging brain pathways - Diffusion MRI: from quantitative measurement to in-vivo neuroanatomy. Diffusion MRI for in-vivo neuroanatomy, Elsevier, Chapter 20 of Section 3, Elsevier Academic Press, Amsterdam

  147. Ward NS, Brown MM, Thompson AJ et al (2003) Neural correlates of outcome after stroke: a cross-sectional fMRI study. Brain Pt 6:1430–1448

    Google Scholar 

  148. Ward NS, Brown MM, Thompson AJ et al (2003) Neural correlates of motor recovery after stroke: a longitudinal fMRI study. Brain Pt 11:2476–2496

    Google Scholar 

  149. Fernandez B, Cardebat D, Demonet JF et al (2004) Functional MRI follow-up study of language processes in healthy subjects and during recovery in a case of aphasia. Stroke 9:2171–2176

    Google Scholar 

  150. Pariente J, Loubinoux I, Carel C et al (2001) Fluoxetine modulates motor performance and cerebral activation of patients recovering from stroke. Ann Neurol 6:718–729

    Google Scholar 

  151. Bjørnehued A and Due-Tønnessen P (2004) Combined fMRI and dynamic perfusion MR in pre-surgical assessment of cerebral arteriovenous malformations. NeuroImage 49

Download references

Acknowledgements

We thank Georg Homola for assisting with data analyses and figure generations. Andreas Bartsch’s work has been generously facilitated by the Vera and Volker Doppelfeld Foundation.

Disclosure

No conflicts of interest.

Author information

Affiliations

  1. Institute of Radiology, Department of Neuroradiology, University Hospital Basel, Petersgraben 4, CH 4031, Basel, Switzerland

    Sven Haller

  2. Institute of Neuroradiology, Department of Imaging and Medical Informatics, Geneva University Hospital, Geneva, Switzerland

    Sven Haller

  3. Department of Neuroradiology, University of Wuerzburg, Wuerzburg, Germany

    Andreas J. Bartsch

  4. Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany

    Andreas J. Bartsch

Authors
  1. Sven Haller
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andreas J. Bartsch
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sven Haller.

Additional information

Haller and Bartsch contributed equally.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Haller, S., Bartsch, A.J. Pitfalls in fMRI. Eur Radiol 19, 2689–2706 (2009). https://doi.org/10.1007/s00330-009-1456-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-009-1456-9

Keywords

  • BOLD
  • Functional MRI
  • fMRI
  • Review