Skip to main content
SpringerLink
Log in

Inter- and Intra-Subject Variability of Neuromagnetic Resting State Networks

  • Original Paper
  • Published:
Brain Topography Aims and scope Submit manuscript

Abstract

Functional connectivity studies conducted at the group level using magnetoencephalography (MEG) suggest that resting state networks (RSNs) emerge from the large-scale envelope correlation structure within spontaneous oscillatory brain activity. However, little is known about the consistency of MEG RSNs at the individual level. This paper investigates the inter- and intra-subject variability of three MEG RSNs (sensorimotor, auditory and visual) using seed-based source space envelope correlation analysis applied to 5 min of resting state MEG data acquired from a 306-channel whole-scalp neuromagnetometer (Elekta Oy, Helsinki, Finland) and source projected with minimum norm estimation. The main finding is that these three MEG RSNs exhibit substantial variability at the single-subject level across and within individuals, which depends on the RSN type, but can be reduced after averaging over subjects or sessions. Over- and under-estimations of true RSNs variability are respectively obtained using template seeds, which are potentially mislocated due to inter-subject variations, and a seed optimization method minimizing variability. In particular, bounds on the minimal number of subjects or sessions required to obtain highly consistent between- or within-subject averages of MEG RSNs are derived. Furthermore, MEG RSN topography positively correlates with their mean connectivity at the inter-subject level. These results indicate that MEG RSNs associated with primary cortices can be robustly extracted from seed-based envelope correlation and adequate averaging. MEG thus appears to be a valid technique to compare RSNs across subjects or conditions, at least when using the current methods.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Anderson JS, Ferguson MA, Lopez-Larson M, Yurgelun-Todd D (2011) Reproducibility of single-subject functional connectivity measurements. AJNR Am J Neuroradiol 32(3):548–555. doi:10.3174/ajnr.A2330

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Birn RM, Molloy EK, Patriat R, Parker T, Meier TB, Kirk GR, Nair VA, Meyerand ME, Prabhakaran V (2013) The effect of scan length on the reliability of resting-state fMRI connectivity estimates. Neuroimage 83:550–558. doi:10.1016/j.neuroimage.2013.05.099

    Article  PubMed Central  PubMed  Google Scholar 

  • Biswal B, Yetkin FZ, Haughton VM, Hyde JS (1995) Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 34(4):537–541

    Article  CAS  PubMed  Google Scholar 

  • Brockwell PJ, Davis RA (1987) Model building and forecasting with ARIMA processes. In: Brockwell PJ, Davis RA (eds) Times series: theory and methods. Springer-Verlag, New York, pp 265–319

    Google Scholar 

  • Brookes MJ, Woolrich M, Luckhoo H, Price D, Hale JR, Stephenson MC, Barnes GR, Smith SM, Morris PG (2011) Investigating the electrophysiological basis of resting state networks using magnetoencephalography. Proc Natl Acad Sci USA 108(40):16783–16788. doi:10.1073/pnas.1112685108

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Brookes MJ, Liddle EB, Hale JR, Woolrich MW, Luckhoo H, Liddle PF, Morris PG (2012a) Task induced modulation of neural oscillations in electrophysiological brain networks. Neuroimage 63(4):1918–1930. doi:10.1016/j.neuroimage.2012.08.012

    Article  CAS  PubMed  Google Scholar 

  • Brookes MJ, Woolrich MW, Barnes GR (2012b) Measuring functional connectivity in MEG: a multivariate approach insensitive to linear source leakage. Neuroimage 63(2):910–920. doi:10.1016/j.neuroimage.2012.03.048

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Carrette E, Op de beeck M, Bourguignon M, Boon P, Vonck K, Legros B, Goldman S, Van Bogaert P, De Tiège X (2011) Recording temporal lobe epileptic activity with MEG in a light-weight magnetic shield. Seizure 20(5):414–418. doi:10.1016/j.seizure.2011.01.015

    Article  PubMed  Google Scholar 

  • Dale AM, Sereno MI (1993) Improved localization of cortical activity by combining EEG and MEG with MRI cortical surface reconstruction: a linear approach. J Cogn Neurosci 5:162–176

    Article  CAS  PubMed  Google Scholar 

  • Damoiseaux JS, Rombouts SA, Barkhof F, Scheltens P, Stam CJ, Smith SM, Beckmann CF (2006) Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci USA 103(37):13848–13853. doi:10.1073/pnas.0601417103

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • de Pasquale F, Della Penna S, Snyder AZ, Lewis C, Mantini D, Marzetti L, Belardinelli P, Ciancetta L, Pizzella V, Romani GL, Corbetta M (2010) Temporal dynamics of spontaneous MEG activity in brain networks. Proc Natl Acad Sci USA 107(13):6040–6045. doi:10.1073/pnas.0913863107

    Article  PubMed Central  PubMed  Google Scholar 

  • de Pasquale F, Della Penna S, Snyder AZ, Marzetti L, Pizzella V, Romani GL, Corbetta M (2012) A cortical core for dynamic integration of functional networks in the resting human brain. Neuron 74(4):753–764. doi:10.1016/j.neuron.2012.03.031

    Article  PubMed Central  PubMed  Google Scholar 

  • De Tiège X, Op de beeck M, Funke M, Legros B, Parkkonen L, Goldman S, Van Bogaert P (2008) Recording epileptic activity with MEG in a light-weight magnetic shield. Epilepsy Res 82(2–3):227–231. doi:10.1016/j.eplepsyres.2008.08.011

    Article  PubMed  Google Scholar 

  • D’Esposito M, Deouell LY, Gazzaley A (2003) Alterations in the BOLD fMRI signal with ageing and disease: a challenge for neuroimaging. Nat Rev Neurosci 4(11):863–872. doi:10.1038/nrn1246

    Article  PubMed  Google Scholar 

  • Deco G, Corbetta M (2011) The dynamical balance of the brain at rest. Neuroscientist 17(1):107–123. doi:10.1177/1073858409354384

    Article  PubMed  Google Scholar 

  • Deco G, Jirsa VK, McIntosh AR (2011) Emerging concepts for the dynamical organization of resting-state activity in the brain. Nat Rev Neurosci 12(1):43–56. doi:10.1038/nrn2961

    Article  CAS  PubMed  Google Scholar 

  • Del Gratta C, Pizzella V, Tecchio F, Romani GL (2001) Magnetoencephalography—a noninvasive brain imaging method with 1 ms time resolution. Rep Prog Phys 64:1759–1814

    Article  Google Scholar 

  • Fox MD, Greicius M (2010) Clinical applications of resting state functional connectivity. Front Syst Neurosci 4:19. doi:10.3389/fnsys.2010.00019

    PubMed Central  PubMed  Google Scholar 

  • Fox MD, Raichle ME (2007) Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 8(9):700–711

    Article  CAS  PubMed  Google Scholar 

  • Hall EL, Robson SE, Morris PG, Brookes MJ (2013a) The relationship between MEG and fMRI. Neuroimage (in press)

  • Hall EL, Woolrich MW, Thomaz CE, Morris PG, Brookes MJ (2013b) Using variance information in magnetoencephalography measures of functional connectivity. Neuroimage 67:203–212. doi:10.1016/j.neuroimage.2012.11.011

    Article  PubMed  Google Scholar 

  • Hämäläinen M, Hari R, Ilmoniemi RJ, Knuutila J, Lounasmaa OV (1993) Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain. Rev Mod Phys 65(2):413–497

    Article  Google Scholar 

  • Hämäläinen M, Lin F, Mosher JC (2010) Anatomically and functionally constrained minimum-norm estimates. In: Hansen PC, Kringelbach ML, Salmelin R (eds) MEG—an introduction to methods. Oxford University Press, New York, pp 186–215

    Chapter  Google Scholar 

  • Hawellek DJ, Schepers IM, Roeder B, Engel AK, Siegel M, Hipp JF (2013) Altered intrinsic neuronal interactions in the visual cortex of the blind. J Neurosci 33(43):17072–17080. doi:10.1523/JNEUROSCI.1625-13.2013

    Article  CAS  PubMed  Google Scholar 

  • Hipp JF, Hawellek DJ, Corbetta M, Siegel M, Engel AK (2012) Large-scale cortical correlation structure of spontaneous oscillatory activity. Nat Neurosci 15(6):884–890. doi:10.1038/nn.3101

    Article  CAS  PubMed  Google Scholar 

  • Hutchison RM, Womelsdorf T, Allen EA, Bandettini PA, Calhoun VD, Corbetta M, Della Penna S, Duyn JH, Glover GH, Gonzalez-Castillo J, Handwerker DA, Keilholz S, Kiviniemi V, Leopold DA, de Pasquale F, Sporns O, Walter M, Chang C (2013) Dynamic functional connectivity: promise, issues, and interpretations. Neuroimage 80:360–378. doi:10.1016/j.neuroimage.2013.05.079

    Article  PubMed  Google Scholar 

  • Lindauer U, Dirnagl U, Fuchtemeier M, Bottiger C, Offenhauser N, Leithner C, Royl G (2010) Pathophysiological interference with neurovascular coupling—when imaging based on hemoglobin might go blind. Front Neuroenerg. doi:10.3389/fnene.2010.00025

    Google Scholar 

  • Liu TT (2013) Neurovascular factors in resting-state functional MRI. Neuroimage 80:339–348. doi:10.1016/j.neuroimage.2013.04.071

    Article  PubMed  Google Scholar 

  • Luckhoo H, Brookes MJ, Heise V, Mackay CE, Ebmeier K, Morris PG, Woolrich MW (2012a) Extracting resting state networks from Elekta Neuromag MEG data using independent component analysis. In: 18th Annual Meeting of the Organization for Human Brain Mapping, Beijing, 2012a

  • Luckhoo H, Hale JR, Stokes MG, Nobre AC, Morris PG, Brookes MJ, Woolrich MW (2012b) Inferring task-related networks using independent component analysis in magnetoencephalography. Neuroimage 62(1):530–541. doi:10.1016/j.neuroimage.2012.04.046

    Article  CAS  PubMed  Google Scholar 

  • Marzetti L, Della Penna S, Snyder AZ, Pizzella V, Nolte G, de Pasquale F, Romani GL, Corbetta M (2013) Frequency specific interactions of MEG resting state activity within and across brain networks as revealed by the multivariate interaction measure. Neuroimage 79:172–183. doi:10.1016/j.neuroimage.2013.04.062

    Article  CAS  PubMed  Google Scholar 

  • Oldfield RC (1971) The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9(1):97–113

    Article  CAS  PubMed  Google Scholar 

  • O’Neill G, Hall E, Corner SP, Morris PG, Brookes MJ (2013) A comparison of beamformer and minimum norm solutions for network mapping in MEG. In: 19th Annual Meeting of the Organization for Human Brain Mapping, Seattle, 2013

  • Raichle ME (2010) Two views of brain function. Trends Cogn Sci 14(4):180–190. doi:10.1016/j.tics.2010.01.008

    Article  PubMed  Google Scholar 

  • Schoffelen JM, Gross J (2009) Source connectivity analysis with MEG and EEG. Hum Brain Mapp 30(6):1857–1865. doi:10.1002/hbm.20745

    Article  PubMed  Google Scholar 

  • Scholvinck ML, Leopold DA, Brookes MJ, Khader PH (2013) The contribution of electrophysiology to functional connectivity mapping. Neuroimage 80:297–306. doi:10.1016/j.neuroimage.2013.04.010

    Article  PubMed  Google Scholar 

  • Stam CJ (2005) Nonlinear dynamical analysis of EEG and MEG: review of an emerging field. Clin Neurophysiol 116(10):2266–2301. doi:10.1016/j.clinph.2005.06.011

    Article  CAS  PubMed  Google Scholar 

  • Taulu S, Simola J, Kajola M (2005) Applications of the signal space separation method. IEEE Trans Signal Process 53:3359–3372

    Article  Google Scholar 

  • Vigario R, Sarela J, Jousmaki V, Hamalainen M, Oja E (2000) Independent component approach to the analysis of EEG and MEG recordings. IEEE Trans Biomed Eng 47(5):589–593. doi:10.1109/10.841330

    Article  CAS  PubMed  Google Scholar 

  • Yan C, Liu D, He Y, Zou Q, Zhu C, Zuo X, Long X, Zang Y (2009) Spontaneous brain activity in the default mode network is sensitive to different resting-state conditions with limited cognitive load. PLoS One 4(5):e5743. doi:10.1371/journal.pone.0005743

    Article  PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgements

Mathieu Bourguignon (research fellow) benefits from a research grant from the Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture (FRIA, FRS-FNRS, Belgium). Catherine Clumeck (research fellow), Alison Mary (research fellow) and Xavier De Tiège (post-doctorate clinical master specialist) benefit from a research grant from the Fonds de la Recherche Scientifique (FRS-FNRS, Belgium). Matthew J. Brookes is funded by a Leverhulme Trust Early Career Fellowship. This work was supported by research grants from the Fonds de la Recherche Scientifique (research conventions: 3.4811.08, 3.4547.10, 3.4554.12; FRS-FNRS, Belgium).

Author information

Authors and Affiliations

  1. Laboratoire de Cartographie fonctionnelle du Cerveau, UNI – ULB Neurosciences Institute, Université libre de Bruxelles (ULB), Brussels, Belgium

    Vincent Wens, Mathieu Bourguignon, Serge Goldman, Brice Marty, Marc Op de Beeck, Catherine Clumeck, Patrick Van Bogaert & Xavier De Tiège

  2. Brain Research Unit, O.V. Lounasmaa Laboratory, Aalto NeuroImaging, School of Science, Aalto University, FI-00076, Aalto, Espoo, Finland

    Mathieu Bourguignon

  3. UR2NF – Neuropsychology and Functional Neuroimaging Research Unit at CRCN – Centre de Recherches Cognition et Neurosciences, and UNI – ULB Neurosciences Institute, Université libre de Bruxelles (ULB), Brussels, Belgium

    Alison Mary & Philippe Peigneux

  4. Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK

    Matthew J. Brookes

Authors
  1. Vincent Wens
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mathieu Bourguignon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Serge Goldman
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Brice Marty
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Marc Op de Beeck
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Catherine Clumeck
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Alison Mary
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Philippe Peigneux
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Patrick Van Bogaert
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Matthew J. Brookes
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Xavier De Tiège
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vincent Wens.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 10378 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wens, V., Bourguignon, M., Goldman, S. et al. Inter- and Intra-Subject Variability of Neuromagnetic Resting State Networks. Brain Topogr 27, 620–634 (2014). https://doi.org/10.1007/s10548-014-0364-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10548-014-0364-8

Keywords

Search

Navigation