Skip to main content

Multimodal Neuroimaging with Simultaneous fMRI and EEG

  • Reference work entry
  • First Online:
Handbook of Neuroengineering

Abstract

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are noninvasive techniques used to measure neural activity in the human brain. fMRI measures the magnetic resonance signal associated with hemodynamic changes driven by neural activity and has a good spatial resolution (2–3 mm isotropic) and low temporal resolution (1–3 s). Whereas EEG is used to record electrical activity in the brain with a millisecond-level temporal resolution but has a limited spatial resolution. By combining fMRI and EEG, it is possible to generate a high spatiotemporal resolution map of human brain function, which is critical for understanding complex dynamics of the human brain. Furthermore, EEG recordings during fMRI can be used to identify the sources of abnormal electrical activity in the brain (e.g., during epileptic seizures). This chapter discusses recent advances in the simultaneous recording of fMRI and EEG in humans. It focuses on the challenges of recording fMRI and EEG simultaneously, techniques for removing artifacts, experimental designs for fMRI and EEG studies, and methods for integrating fMRI and EEG data.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 949.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 999.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Ives, J.R., et al.: Monitoring the patient’s EEG during echo planar MRI. Electroencephalogr. Clin. Neurophysiol. 87(6), 417–420 (1993)

    Google Scholar 

  2. Goldman, R.I., et al.: Acquiring simultaneous EEG and functional MRI. Clin. Neurophysiol. 111(11), 1974–1980 (2000)

    Google Scholar 

  3. Abreu, R., Leal, A., Figueiredo, P.: EEG-informed fMRI: a review of data analysis methods. Front. Hum. Neurosci. 12, 29 (2018)

    Google Scholar 

  4. Simoes, M., et al.: Correlated alpha activity with the facial expression processing network in a simultaneous EEG-fMRI experiment. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2017, 2562–2565 (2017)

    Google Scholar 

  5. Poudel, G.R., et al.: Losing the struggle to stay awake: divergent thalamic and cortical activity during microsleeps. Hum. Brain Mapp. 35(1), 257–269 (2014)

    Google Scholar 

  6. Noth, U., et al.: Simultaneous electroencephalography-functional MRI at 3 t: an analysis of safety risks imposed by performing anatomical reference scans with the EEG equipment in place. J. Magn. Reson. Imaging. 35(3), 561–571 (2012)

    Google Scholar 

  7. Huster, R.J., et al.: Methods for simultaneous EEG-fMRI: an introductory review. J. Neurosci. 32(18), 6053–6060 (2012)

    Google Scholar 

  8. Michels, L., et al.: Simultaneous EEG-fMRI during a working memory task: modulations in low and high frequency bands. PLoS One. 5(4), e10298 (2010)

    Google Scholar 

  9. Kaufmann, C., et al.: Brain activation and hypothalamic functional connectivity during human non-rapid eye movement sleep: an EEG/fMRI study. Brain. 129(Pt 3), 655–667 (2006)

    Google Scholar 

  10. Laufs, H., et al.: EEG-correlated fMRI of human alpha activity. NeuroImage. 19(4), 1463–1476 (2003)

    Google Scholar 

  11. Goldman, R.I., et al.: Simultaneous EEG and fMRI of the alpha rhythm. NeuroReport. 13(18), 2487–2492 (2002)

    Google Scholar 

  12. Liu, Z.M., He, B.: FMRI-EEG integrated cortical source imaging by use of time-variant spatial constraints. NeuroImage. 39(3), 1198–1214 (2008)

    Google Scholar 

  13. Poudel, G.R., Innes, C.R.H., Jones, R.D.: Distinct neural correlates of time-on-task and transient errors during a visuomotor tracking task after sleep restriction. NeuroImage. 77, 105–113 (2013)

    Google Scholar 

  14. Poudel, G.R., Innes, C.R.H., Jones, R.D.: Temporal evolution of neural activity and connectivity during microsleeps when rested and following sleep restriction. NeuroImage. 174, 263–273 (2018)

    Google Scholar 

  15. Ogawa, S., et al.: Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc. Natl. Acad. Sci. 87, 9868–9872 (1990)

    Google Scholar 

  16. Arthurs, O.J., Boniface, S.: How well do we understand the neural origins of the fMRI bold signal? Trends Neurosci. 25(3), 169–169 (2002)

    Google Scholar 

  17. Salek-Haddadi, A., et al.: Studying spontaneous EEG activity with fMRI. Brain Res. Rev. 43(1), 110–133 (2003)

    Google Scholar 

  18. Buxton, R.B., Wong, E.C., Frank, L.R.: Dynamics of blood flow and oxygenation changes during brain activation; the balloon model. Magn. Reson. Med. 39, 855–864 (1998)

    Google Scholar 

  19. Logothetis, N.K., et al.: Neurophysiological investigation of the basis of the fMRI signal. Nature. 412(6843), 150–157 (2001)

    Google Scholar 

  20. Lindquist, M.A., et al.: Modeling the hemodynamic response function in fMRI: efficiency, bias and mis-modeling. NeuroImage. 45(1 Suppl), S187–S198 (2009)

    Google Scholar 

  21. Menon, R.S., et al.: BOLD based functional MRI at 4 Tesla includes a capillary bed contribution: echo-planar imaging correlates with previous optical imaging using intrinsic signals. Magn. Reson. Med. 33(3), 453 (1995)

    Google Scholar 

  22. Hu, X., Yacoub, E.: The story of the initial dip in fMRI. NeuroImage. 62(2), 1103–1108 (2012)

    Google Scholar 

  23. Gras, V., et al.: Optimizing bold sensitivity in the 7t human connectome project resting-state fMRI protocol using plug-and-play parallel transmission. NeuroImage. 195, 1–10 (2019)

    Google Scholar 

  24. Kim, S.-G., Ogawa, S.: Insights into new techniques for high resolution functional MRI. Curr. Opin. Neurobiol. 12(5), 607–615 (2002)

    Google Scholar 

  25. Kashyap, S., et al.: Resolving laminar activation in human v1 using ultra-high spatial resolution fMRI at 7t. Sci. Rep. 8, 17063 (2018)

    Google Scholar 

  26. Tsuchida, T.N., et al.: American clinical neurophysiology society: EEG guidelines introduction. J. Clin. Neurophysiol. 33(4), 301–302 (2016)

    Google Scholar 

  27. Kirschstein, T., Kohling, R.: What is the source of the EEG? Clin. EEG Neurosci. 40(3), 146–149 (2009)

    Google Scholar 

  28. Buzsaki, G., Anastassiou, C.A., Koch, C.: The origin of extracellular fields and currents--EEG, ECOG, LFP and spikes. Nat. Rev. Neurosci. 13(6), 407–420 (2012)

    Google Scholar 

  29. Cajochen, C., Foy, R., Dijk, D.J.: Frontal predominance of a relative increase in sleep delta and theta EEG activity after sleep loss in humans. Sleep Res. Online. 2(3), 65–69 (1999)

    Google Scholar 

  30. Accolla, E.A., et al.: Clinical correlates of frontal intermittent rhythmic delta activity (FIRDA). Clin. Neurophysiol. 122(1), 27–31 (2011)

    Google Scholar 

  31. Makeig, S., Jung, T.P., Sejnowski, T.J.: Awareness during drowsiness: dynamics and electrophysiological correlates. Can. J. Exp. Psychol. 54(4), 266–273 (2000)

    Google Scholar 

  32. Makeig, S., Jung, T.P.: Tonic, phasic, and transient EEG correlates of auditory awareness in drowsiness. Brain Res. Cogn. Brain Res. 4(1), 15–25 (1996)

    Google Scholar 

  33. Brueggen, K., et al.: Early changes in alpha band power and dmn bold activity in Alzheimer’s disease: a simultaneous resting state EEG-fMRI study. Front. Aging Neurosci. 9, 319 (2017)

    Google Scholar 

  34. Dang-Vu, T.T., et al.: Spontaneous neural activity during human slow wave sleep. Proc. Natl. Acad. Sci. U. S. A. 105(39), 15160–15165 (2008)

    Google Scholar 

  35. Liu, Y., et al.: Top-down modulation of neural activity in anticipatory visual attention: control mechanisms revealed by simultaneous EEG-fMRI. Cereb. Cortex. 26(2), 517–529 (2016)

    Google Scholar 

  36. Mullinger, K., et al.: Effects of simultaneous EEG recording on MRI data quality at 1.5, 3 and 7 tesla. Int. J. Psychophysiol. 67(3), 178–188 (2008)

    Google Scholar 

  37. Hawsawi, H.B., Carmichael, D.W., Lemieux, L.: Safety of simultaneous scalp or intracranial EEG during MRI: a review. Front. Phys. 5, 42 (2017)

    Google Scholar 

  38. Lemieux, L., et al.: Recording of EEG during fMRI experiments: patient safety. Magn. Reson. Med. 38(6), 943–952 (1997)

    Google Scholar 

  39. Salek-Haddadi, A., et al.: EEG quality during simultaneous functional MRI of interictal epileptiform discharges. Magn. Reson. Imaging. 21(10), 1159–1166 (2003)

    Google Scholar 

  40. Srivastava, G., et al.: Ica-based procedures for removing ballistocardiogram artifacts from EEG data acquired in the MRI scanner. NeuroImage. 24(1), 50–60 (2005)

    Google Scholar 

  41. Jonmohamadi, Y., et al.: Source-space ICA for EEG source separation, localization, and time-course reconstruction. NeuroImage. 101, 720–737 (2014)

    Google Scholar 

  42. Toppi, J., et al.: Time-varying effective connectivity of the cortical neuroelectric activity associated with behavioural microsleeps. NeuroImage. 124(Pt A), 421–432 (2016)

    Google Scholar 

  43. Bayer, M., Rubens, M.T., Johnstone, T.: Simultaneous EEG-fMRI reveals attention-dependent coupling of early face processing with a distributed cortical network. Biol. Psychol. 132, 133–142 (2018)

    Google Scholar 

  44. Bonmassar, G., et al.: Spatiotemporal brain imaging of visual-evoked activity using interleaved EEG and fMRI recordings. NeuroImage. 13(6), 1035–1043 (2001)

    Google Scholar 

  45. Portas, C.M., et al.: Auditory processing across the sleep-wake cycle: simultaneous EEG and fMRI monitoring in humans. Neuron. 28(3), 991–999 (2000)

    Google Scholar 

  46. Menon, V., Crottaz-Herbette, S.: Combined EEG and fMRI studies of human brain function. Neuroimaging. 66(Pt A), 291 (2005)

    Google Scholar 

  47. Hall, D.A., et al.: “Sparse” temporal sampling in auditory fMRI. Hum. Brain Mapp. 7(3), 213–223 (1999)

    Google Scholar 

  48. Schwarzbauer, C., et al.: Interleaved silent steady state (ISSS) imaging: a new sparse imaging method applied to auditory fMRI. NeuroImage. 29(3), 774–782 (2006)

    Google Scholar 

  49. Poudel, G.R., et al.: Neural correlates of decision-making during a Bayesian choice task. NeuroReport. 28(4), 193–199 (2017)

    MathSciNet  Google Scholar 

  50. McGlashan, E.M., et al.: Imaging individual differences in the response of the human suprachiasmatic area to light. Front. Neurol. 9, 1022 (2018)

    Google Scholar 

  51. Schabus, M., et al.: Neural correlates of sleep spindles as revealed by simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). J. Sleep Res. 15, 50–51 (2006)

    Google Scholar 

  52. Fang, L., et al.: Simultaneous EEG-fMRI reveals spindle-related neural correlates of human intellectual abilities during NREM sleep. Sleep Med. 40, E99–E99 (2017)

    Google Scholar 

  53. Mullinger, K.J., Castellone, P., Bowtell, R.: Best current practice for obtaining high quality EEG data during simultaneous fMRI. J. Vis. Exp. (76) (2013)

    Google Scholar 

  54. Allen, P.J., Josephs, O., Turner, R.: A method for removing imaging artifact from continuous EEG recorded during functional MRI. NeuroImage. 12(2), 230–239 (2000)

    Google Scholar 

  55. Negishi, M., et al.: Removal of time-varying gradient artifacts from EEG data acquired during continuous fMRI. Clin. Neurophysiol. 115(9), 2181–2192 (2004)

    Google Scholar 

  56. Niazy, R.K., et al.: Removal of fMRI environment artifacts from EEG data using optimal basis sets. NeuroImage. 28(3), 720–737 (2005)

    Google Scholar 

  57. Ritter, P., Villringer, A.: Simultaneous EEG-fMRI. Neurosci. Biobehav. Rev. 30(6), 823–838 (2006)

    Google Scholar 

  58. Chowdhury, M.E.H., et al.: Simultaneous EEG-fMRI: evaluating the effect of the EEG cap-cabling configuration on the gradient artifact. Front. Neurosci. 13, 690 (2019)

    Google Scholar 

  59. Cunningham, C.J.B., et al.: Simultaneous EEG-fMRI in human epilepsy. Can. J. Neurol. Sci. 35(4), 420–435 (2008)

    Google Scholar 

  60. Sartori, E., et al.: Gradient artifact removal in co-registration EEG/fMRI. World Congress on Medical Physics and Biomedical Engineering, Vol 25, Pt 4: Image Processing, Biosignal Processing, Modelling and Simulation. Biomechanics. 25, 1143–1146 (2010)

    Google Scholar 

  61. Freyer, F., et al.: Ultrahigh-frequency EEG during fMRI: pushing the limits of imaging-artifact correction. NeuroImage. 48(1), 94–108 (2009)

    Google Scholar 

  62. de Munck, J.C., et al.: The hemodynamic response of the alpha rhythm: an EEG/fMRI study. NeuroImage. 35(3), 1142–1151 (2007)

    Google Scholar 

  63. Moosmann, M., et al.: Realignment parameter-informed artefact correction for simultaneous EEG-fMRI recordings. NeuroImage. 45(4), 1144–1150 (2009)

    Google Scholar 

  64. Ryali, S., et al.: Development, validation, and comparison of ICA-based gradient artifact reduction algorithms for simultaneous EEG-spiral in/out and echo-planar fMRI recordings. NeuroImage. 48(2), 348–361 (2009)

    Google Scholar 

  65. Mantini, D., et al.: Complete artifact removal for EEG recorded during continuous fMRI using independent component analysis. NeuroImage. 34(2), 598–607 (2007)

    Google Scholar 

  66. Chechile, R.A.: Independent component analysis: a tutorial introduction. J. Math. Psychol. 49(5), 426–426 (2005)

    MathSciNet  Google Scholar 

  67. Islam, M.K., Rastegarnia, A., Yang, Z.: Methods for artifact detection and removal from scalp EEG: a review. Clin. Neurophysiol. 46(4-5), 287–305 (2016)

    Google Scholar 

  68. Acharjee, P.P., et al.: Independent vector analysis for gradient artifact removal in concurrent EEG-fMRI data. IEEE Trans. Biomed. Eng. 62(7), 1750–1758 (2015)

    Google Scholar 

  69. Chowdhury, M.E.H., et al.: Reference layer artefact subtraction (RLAS): a novel method of minimizing EEG artefacts during simultaneous fMRI (vol 84, pg 307, 2014). NeuroImage. 98, 547–547 (2014)

    Google Scholar 

  70. Maziero, D., et al.: Towards motion insensitive EEG-fMRI: correcting motion-induced voltages and gradient artefact instability in EEG using an fMRI prospective motion correction (PMC) system. NeuroImage. 138, 13–27 (2016)

    Google Scholar 

  71. van der Meer, J.N., et al.: Carbon-wire loop based artifact correction outperforms post-processing EEG/fMRI corrections-a validation of a real-time simultaneous EEG/fMRI correction method. NeuroImage. 125, 880–894 (2016)

    Google Scholar 

  72. Abbott, D.E., et al.: Constructing carbon fiber motion-detection loops for simultaneous EEG-fMRI. Front. Neurol. 5, 260 (2015)

    Google Scholar 

  73. Debener, S., et al.: Properties of the ballistocardiogram artefact as revealed by EEG recordings at 1.5, 3 and 7 t static magnetic field strength. Int. J. Psychophysiol. 67(3), 189–199 (2008)

    Google Scholar 

  74. Grouiller, F., et al.: A comparative study of different artefact removal algorithms for EEG signals acquired during functional MRI. NeuroImage. 38(1), 124–137 (2007)

    Google Scholar 

  75. Wang, K., et al.: Clustering-constrained ICA for ballistocardiogram artifacts removal in simultaneous EEG-fMRI. Front. Neurosci. 12, 59 (2018)

    Google Scholar 

  76. Mayeli, A., et al.: Real-time EEG artifact correction during fMRI using ICA. J. Neurosci. Methods. 274, 27–37 (2016)

    Google Scholar 

  77. Masterton, R.A.J., et al.: Measurement and reduction of motion and ballistocardiogram artefacts from simultaneous EEG and fMRI recordings. NeuroImage. 37(1), 202–211 (2007)

    Google Scholar 

  78. Valdes-Sosa, P.A., et al.: Model driven EEG/fMRI fusion of brain oscillations. Hum. Brain Mapp. 30(9), 2701–2721 (2009)

    Google Scholar 

  79. Dong, L., et al.: Simultaneous EEG-fMRI: trial level spatio-temporal fusion for hierarchically reliable information discovery. NeuroImage. 99, 28–41 (2014)

    Google Scholar 

  80. Daunizeau, J., et al.: Symmetrical event-related EEG/fMRI information fusion in a variational Bayesian framework. NeuroImage. 36(1), 69–87 (2007)

    Google Scholar 

  81. Singh, M., Patel, P., Al-Dayeh, L.: FMRI of brain activity during alpha rhythm. International Society for Magnetic Resonance in Medicine, Concord, CA (1998)

    Google Scholar 

  82. Omata, K., et al.: Spontaneous slow fluctuation of EEG alpha rhythm reflects activity in deep-brain structures: a simultaneous EEG-fMRI study. PLoS One. 8(6), e66869 (2013)

    Google Scholar 

  83. Ragazzoni, A., et al.: “Hit the missing stimulus”. A simultaneous EEG-fMRI study to localize the generators of endogenous ERPs in an omitted target paradigm. Sci. Rep. 9, 3684 (2019)

    Google Scholar 

  84. Scheeringa, R., et al.: Frontal theta EEG activity correlates negatively with the default mode network in resting state. Int. J. Psychophysiol. 67(3), 242–251 (2008)

    Google Scholar 

  85. Jann, K., et al.: Bold correlates of EEG alpha phase-locking and the fMRI default mode network. NeuroImage. 45(3), 903–916 (2009)

    Google Scholar 

  86. Calhoun, V.D., et al.: Neuronal chronometry of target detection: fusion of hemodynamic and event-related potential data. NeuroImage. 30(2), 544–553 (2006)

    Google Scholar 

  87. Moosmann, M., et al.: Joint independent component analysis for simultaneous EEG-fMRI: principle and simulation. Int. J. Psychophysiol. 67(3), 212–221 (2008)

    Google Scholar 

  88. McKeown, M.J., et al.: Analysis of fMRI data by blind separation into independent spatial components. Hum. Brain Mapp. 6(3), 160–188 (1998)

    Google Scholar 

  89. Kincses, Z.T., et al.: Model-free characterization of brain functional networks for motor sequence learning using fMRI. NeuroImage. 39(4), 1950–1958 (2008)

    Google Scholar 

  90. Habas, C., Cabanis, E.A.: Dissociation of the neural networks recruited during a haptic object-recognition task: complementary results with a tensorial independent component analysis. Am. J. Neuroradiol. 29(9), 1715–1721 (2008)

    Google Scholar 

  91. Damoiseaux, J.S., et al.: Consistent resting-state networks across healthy subjects. Proc. Natl. Acad. Sci. U. S. A. 103(37), 13848–13853 (2006)

    Google Scholar 

  92. Jonmohamadi, Y., et al.: Constrained temporal parallel decomposition for EEG-fMRI fusion. J. Neural Eng. 16(1), 016017 (2019)

    Google Scholar 

  93. Laufs, H., et al.: Where the BOLD signal goes when alpha EEG leaves. NeuroImage. 31, 1408 (2006)

    Google Scholar 

  94. Spiers, H.J., Maguire, E.A.: Neural substrates of driving behaviour. NeuroImage. 36(1), 245–255 (2007)

    Google Scholar 

  95. Hutchison, K., et al.: Cortical activation can be visualized during sleep using simultaneous EEG-fMRI. Sleep. 30, A36–A37 (2007)

    Google Scholar 

  96. Culham, J.C.: Functional neuroimaging: experimental design and analysis. In: Handbook of Functional Neuroimaging of Cognition, pp. 53–82. MIT Press, Cambridge, MA (2006)

    Google Scholar 

  97. Dale, A.M.: Optimal experimental design for event-related fMRI. Hum. Brain Mapp. 8(2-3), 109–114 (1999)

    Google Scholar 

  98. Hopfinger, J.B., Buonocore, M.H., Mangun, G.R.: The neural mechanisms of top-down attentional control. Nat. Neurosci. 3, 284–291 (2000)

    Google Scholar 

  99. Weissman, D., et al.: The neural bases of momentary lapses in attention. Nat. Neurosci. 9, 971–978 (2006)

    Google Scholar 

  100. Mechelli, A., et al.: Comparing event-related and epoch analysis in blocked design fMRI. NeuroImage. 18(3), 806–810 (2003)

    Google Scholar 

  101. Visscher, K.M., et al.: Mixed blocked/event-related designs separate transient and sustained activity in fMRI. NeuroImage. 19(4), 1694–1708 (2003)

    Google Scholar 

  102. Fox, M.D., et al.: The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl. Acad. Sci. 102(27), 9673–9678 (2005)

    Google Scholar 

  103. Critchley, H.D., et al.: Neural activity relating to generation and representation of galvanic skin conductance responses: a functional magnetic resonance imaging study. J. Neurosci. 20(8), 3033 (2000)

    Google Scholar 

  104. Spiers, H., Maguire, E.: Decoding human brain activity during real-world experiences. Trends Cogn. Sci. 11(8), 356–365 (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Govinda R. Poudel .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 Springer Nature Singapore Pte Ltd.

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Poudel, G.R., Jones, R.D. (2023). Multimodal Neuroimaging with Simultaneous fMRI and EEG. In: Thakor, N.V. (eds) Handbook of Neuroengineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-5540-1_81

Download citation

Publish with us

Policies and ethics