Brain Topography

, Volume 27, Issue 3, pp 338–352 | Cite as

Low-Dimensional Dynamics of Resting-State Cortical Activity

  • Saeid Mehrkanoon
  • Michael Breakspear
  • Tjeerd W. Boonstra
Original Paper


Endogenous brain activity supports spontaneous human thought and shapes perception and behavior. Connectivity-based analyses of endogenous, or resting-state, functional magnetic resonance imaging (fMRI) data have revealed the existence of a small number of robust networks which have a rich spatial structure. Yet the temporal information within fMRI data is limited, motivating the complementary analysis of electrophysiological recordings such as electroencephalography (EEG). Here we provide a novel method based on multivariate time–frequency interdependence to reconstruct the principal resting-state network dynamics in human EEG data. The stability of network expression across subjects is assessed using resampling techniques. We report the presence of seven robust networks, with distinct topographic organizations and high frequency (∼5–45 Hz) fingerprints, nested within slow temporal sequences that build up and decay over several orders of magnitude. Interestingly, all seven networks are expressed concurrently during these slow dynamics, although there is a temporal asymmetry in the pattern of their formation and dissolution. These analyses uncover the complex temporal character of endogenous cortical fluctuations and, in particular, offer an opportunity to reconstruct the low dimensional linear subspace in which they unfold.


Resting-state network Functional connectivity Neuronal synchronization Electroencephalography 



This research was supported by the ARC Thinking Systems grant TS0669860; the National Health and Medical Research Council; BrainNRG collaborative award JSMF22002082, and the Netherlands Organization for Scientific Research (NWO #45110-030). The authors wish to thank Angela Langdon and James Roberts for their comments on a draft manuscript.

Supplementary material

10548_2013_319_MOESM1_ESM.jpg (4.1 mb)
Supplementary material 1 (JPEG 4 MB)
10548_2013_319_MOESM2_ESM.png (867 kb)
Supplementary material 2 (PNG 867 kb)


  1. Akalin Acar Z, Makeig S (2013) Effects of forward model errors on EEG source localization. Brain Topogr 26(3):378–396PubMedCentralPubMedCrossRefGoogle Scholar
  2. Aquino KM, Schira MM, Robinson PA, Drysdale PM, Breakspear M (2012) Hemodynamic traveling waves in human visual cortex. PLoS Comput Biol 8(3):e1002435Google Scholar
  3. Ashwin P, Chossat P (1998) Attractors for robust heteroclinic cycles with continua of connections. J Nonlinear Sci 8(2):103–129CrossRefGoogle Scholar
  4. Banerjee A, Tognoli E, Assisi C, Kelso J, Jirsa V (2008) Mode level cognitive subtraction (MLCS) quantifies spatiotemporal reorganization in large-scale brain topographies. NeuroImage 42(2):663–674PubMedCentralPubMedCrossRefGoogle Scholar
  5. Beckmann C, DeLuca M, Devlin J, Smith S (2005) Investigations into resting-state connectivity using independent component analysis. Philos Trans R Soc B 360(1457):1001–1013CrossRefGoogle Scholar
  6. Birn R, Diamond J, Smith MA, Bandettini P (2006) Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI. NeuroImage 31(4):1536–1548PubMedCrossRefGoogle Scholar
  7. Biswal B, Yetkin F, Haughton V, Hyde J (1995) Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 34(4):537–541PubMedCrossRefGoogle Scholar
  8. Boonstra TW, Daffertshofer A, Breakspear M, Beek JP (2007) Multivariate time–frequency analysis of electromagnetic brain activity during bimanual motor learning. NeuroImage 36(2):370–377PubMedCrossRefGoogle Scholar
  9. Breakspear M (2002) Nonlinear phase desynchronization in human electroencephalographic data. Human Brain Mapp 15(3):175–198CrossRefGoogle Scholar
  10. Britz J, Van De Ville D, Michel C (2010) Bold correlates of EEG topography reveal rapid resting-state network dynamics. NeuroImage 52(4):1162–1170PubMedCrossRefGoogle Scholar
  11. Brookes M, Woolrich M, Luckhoo H, Price D, Hale J, Stephenson M, Barnes G, Smith S, Morris P (2011) Investigating the electrophysiological basis of resting state networks using magnetoencephalography. Proc Natl Acad Sci USA 108(40):16783–16788Google Scholar
  12. Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10(3):186–198PubMedCrossRefGoogle Scholar
  13. Buzsaki G, Draguhn A (2004) Neuronal oscillations in cortical networks. Science 304:1926–1929PubMedCrossRefGoogle Scholar
  14. Cardoso JF (1997) Infomax and maximum likelihood for blind source separation. IEEE Signal Process Lett 4(4):112–114CrossRefGoogle Scholar
  15. Carter G (1987) Coherence and time delay estimation. Proc IEEE 75(2):236–255CrossRefGoogle Scholar
  16. Cole D, Smith S, Beckmann C (2010) Advances and pitfalls in the analysis and interpretation of resting-state fMRI data. Front Syst Neurosci 4:1–15Google Scholar
  17. Daffertshofer A, Lamoth C, Meijer O, Beek P (2004) PCA in studying coordination and variability: a tutorial. Clin Biomech 19(4):415–428CrossRefGoogle Scholar
  18. Damoiseaux J, Rombouts S, Barkhof F, Scheltens P, Stam C, Smith S, Beckmann C (2006) Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci USA 103(37):13848–13853Google Scholar
  19. Daunizeau J, Friston K, Kiebel S (2009) Variational bayesian identification and prediction of stochastic nonlinear dynamic causal models. Physica D 238(21):2089–2118PubMedCentralPubMedCrossRefGoogle Scholar
  20. De Pasquale F, Della Penna S, Snyder A, Lewis C, Mantini D, Marzetti L, Belardinelli P, Ciancetta L, Pizzella V, Romani G, Corbetta M (2010) Temporal dynamics of spontaneous MEG activity in brain networks. Proc Natl Acad Sci USA 107(13):6040–6045PubMedCentralPubMedCrossRefGoogle Scholar
  21. Deco G, Jirsa V (2012) Ongoing cortical activity at rest: criticality, multistability, and ghost attractors. J Neurosci 32(10):3366–3375PubMedCrossRefGoogle Scholar
  22. Deco G, Jirsa V, McIntosh A, Sporns O, Kötter R (2009) Key role of coupling, delay, and noise in resting brain fluctuations. Proc Natl Acad Sci USA 106(29):12207–12212Google Scholar
  23. Dehghani N, Bédard C, Cash S, Halgren E, Destexhe A (2010) Comparative power spectral analysis of simultaneous elecroencephalographic and magnetoencephalographic recordings in humans suggests non-resistive extracellular media. J Comput Neurosci 29(3):405–421PubMedCentralPubMedCrossRefGoogle Scholar
  24. Efron B, Petrosian V (1999) Nonparametric methods for doubly truncated data. J Am Stat Assoc 94(447):824–834CrossRefGoogle Scholar
  25. Engel A, König P, Kreiter A, Singer W (1991) Interhemispheric synchronization of oscillatory neuronal responses in cat visual cortex. Science 252(5009):1177–1179PubMedCrossRefGoogle Scholar
  26. Fein G, Raz J, Brown F, Merrin E (1988) Common reference coherence data are confounded by power phase effects. Electroencephalogr Clin Neurophysiol 69(6):581–584PubMedCrossRefGoogle Scholar
  27. Fleuriet J, Goffart L (2012) Saccadic interception of a moving visual target after a spatiotemporal perturbation. J Neurosci 32(2):452–461PubMedCrossRefGoogle Scholar
  28. Fox M, Raichle M (2007) Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 8(9):700–711PubMedCrossRefGoogle Scholar
  29. Fox M, Snyder A, Vincent J, Corbetta M, Van Essen D, Raichle M (2005) The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci USA 102(27):9673–9678PubMedCentralPubMedCrossRefGoogle Scholar
  30. Fox M, Snyder A, Vincent J, Raichle M (2007) Intrinsic fluctuations within cortical systems account for intertrial variability in human behavior. Neuron 56(1):171–184PubMedCrossRefGoogle Scholar
  31. Freyer F, Aquino K, Robinson PA, Ritter P, Breakspear M (2009) Bistability and non-gaussian fluctuations in spontaneous cortical activity. J Neurosci 29(26):8512–8524PubMedCrossRefGoogle Scholar
  32. Freyer F, Roberts J, Becker R, Robinson P, Ritter P, Breakspear M (2011) Biophysical mechanisms of multistability in resting-state cortical rhythms. J Neurosci 31(17):6353–6361PubMedCrossRefGoogle Scholar
  33. Freyer F, Roberts J, Ritter P, Breakspear M (2012) A canonical model of multistability and scale-invariance in biological systems. PLoS Comput Biol 8(8):e1002634Google Scholar
  34. Fries P (2005) A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends Cogn Sci 9(10):474–480PubMedCrossRefGoogle Scholar
  35. Friston K (2002) Functional integration and inference in the brain. Prog Neurobiol 68(2):113–143PubMedCrossRefGoogle Scholar
  36. Friston K, Li B, Daunizeau J, Stephan K (2011) Network discovery with dcm. NeuroImage 56(3):1202–1221PubMedCentralPubMedCrossRefGoogle Scholar
  37. Ganzetti M, Mantini D (2013) Functional connectivity and oscillatory neuronal activity in the resting human brain. Neuroscience 240:297–309PubMedCrossRefGoogle Scholar
  38. Ghosh A, Rho Y, McIntosh A, Kötter R, Jirsa V (2008) Noise during rest enables the exploration of the brain’s dynamic repertoire. PLoS Comput Biol 4(10):e1000196Google Scholar
  39. Greicius M, Krasnow B, Reiss A, Menon V (2003) Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci USA 100(1):253–258PubMedCentralPubMedCrossRefGoogle Scholar
  40. Gross J, Kujala J, Hämäläinen M, Timmermann L, Schnitzler A, Salmelin R (2001) Dynamic imaging of coherent sources: studying neural interactions in the human brain. Proc Natl Acad Sci USA 98(2):694–699PubMedCentralPubMedCrossRefGoogle Scholar
  41. He B, Raichle M (2009) The fMRI signal, slow cortical potential and consciousness. Trends Cogn Sci 13(7):302–309PubMedCentralPubMedCrossRefGoogle Scholar
  42. Heitmann S, Gong P, Breakspear M (2012) A computational role for bistability and traveling waves in motor cortex. Front Comput Neurosci 6:1–15Google Scholar
  43. Hillebrand A, Barnes G, Bosboom J, Berendse H, Stam C (2012) Frequency-dependent functional connectivity within resting-state networks: an atlas-based MEG beamformer solution. NeuroImage 59(4):3909–3921PubMedCentralPubMedCrossRefGoogle Scholar
  44. Hipp J, Hawellek D, Corbetta M, Siegel M, Engel A (2012) Large-scale cortical correlation structure of spontaneous oscillatory activity. Nat Neurosci 15(6):884–890PubMedCrossRefGoogle Scholar
  45. Honey CJ, Kötter R, Breakspear M, Sporns O (2007) Network structure of cerebral cortex shapes functional connectivity on multiple time scales. Proc Natl Acad Sci USA 104(24):10240–10245Google Scholar
  46. Jin SH, Jeong W, Seol J, Kwon J, Chung C (2013) Functional cortical hubs in the eyes-closed resting human brain from an electrophysiological perspective using magnetoencephalography. PLoS ONE 8(7):e68192Google Scholar
  47. Khader P, Schicke T, Röder B, Rösler F (2008) On the relationship between slow cortical potentials and bold signal changes in humans. Int J Psychophysiol 67(3):252–261PubMedCrossRefGoogle Scholar
  48. Kobayashi T, Misaki K, Nakagawa H, Madokoro S, Ihara H, Tsuda K, Umezawa Y, Murayama J, Isaki K (1999) Non-linear analysis of the sleep EEG. Psychiatry Clin Neurosci 53(2):159–161PubMedCrossRefGoogle Scholar
  49. Laufs H, Kleinschmidt A, Beyerle A, Eger E, Salek-Haddadi A, Preibisch C, Krakow K (2003) EEG-correlated fMRI of human alpha activity. NeuroImage 19(4):1463–1476PubMedCrossRefGoogle Scholar
  50. Lehmann D, Michel C (1989) Intracerebral dipole sources of EEG FFT power maps. Brain Topography 2(1–2):155–164PubMedCrossRefGoogle Scholar
  51. Lewis C, Baldassarre A, Committeri G, Romani G, Corbetta M (2009) Learning sculpts the spontaneous activity of the resting human brain. Proc Natl Acad Sci USA 106(41):17558–17563Google Scholar
  52. Linkenkaer-Hansen K, Nikouline V, Palva J, Ilmoniemi R (2001) Long-range temporal correlations and scaling behavior in human brain oscillations. J Neurosci 21(4):1370–1377PubMedGoogle Scholar
  53. Mantini D, Perrucci M, Del Gratta C, Romani G, Corbetta M (2007) Electrophysiological signatures of resting state networks in the human brain. Proc Natl Acad Sci USA 104(32):13170–13175Google Scholar
  54. Mason M, Norton M, Van Horn J, Wegner D, Grafton S, Macrae C (2007) Wandering minds: the default network and stimulus-independent thought. Science 315(5810):393–395PubMedCentralPubMedCrossRefGoogle Scholar
  55. McIntosh A, Lobaugh N (2004) Partial least squares analysis of neuroimaging data: applications and advances. NeuroImage 23(suppl. 1):S250–S263PubMedCrossRefGoogle Scholar
  56. Mehrkanoon S, Breakspear M, Daffertshofer A, Boonstra TW (2013) Non-identical smoothing operators for estimating time–frequency interdependence in electrophysiological recordings. EURASIP J Adv Signal Process 2013(73):1–16Google Scholar
  57. Miller K, Weaver K, Ojemann J (2009) Direct electrophysiological measurement of human default network areas. Proc Natl Acad Sci USA 106(29):12174–12177Google Scholar
  58. Moosmann M, Ritter P, Krastel I, Brink A, Thees S, Blankenburg F, Taskin B, Obrig H, Villringer A (2003) Correlates of alpha rhythm in functional magnetic resonance imaging and near infrared spectroscopy. NeuroImage 20(1):145–158PubMedCrossRefGoogle Scholar
  59. Musso F, Brinkmeyer J, Mobascher A, Warbrick T, Winterer G (2010) Spontaneous brain activity and EEG microstates. A novel EEG/fMRI analysis approach to explore resting-state networks. NeuroImage 52(4):1149–1161PubMedCrossRefGoogle Scholar
  60. Nir Y, Mukamel R, Dinstein I, Privman E, Harel M, Fisch L, Gelbard-Sagiv H, Kipervasser S, Andelman F, Neufeld M, Kramer U, Arieli A, Fried I, Malach R (2008) Interhemispheric correlations of slow spontaneous neuronal fluctuations revealed in human sensory cortex. Nat Neurosci 11(9):1100–1108PubMedCentralPubMedCrossRefGoogle Scholar
  61. Nolte G, Bai O, Wheaton L, Mari Z, Vorbach S, Hallett M (2004) Identifying true brain interaction from EEG data using the imaginary part of coherency. Clin Neurophysiol 115(10):2292–2307PubMedCrossRefGoogle Scholar
  62. Nunez P, Srinivasan R (2006) A theoretical basis for standing and traveling brain waves measured with human eeg with implications for an integrated consciousness. Clin Neurophysiol 117(11):2424–2435PubMedCentralPubMedCrossRefGoogle Scholar
  63. Perdikis D, Huys R, Jirsa V (2011) Complex processes from dynamical architectures with time-scale hierarchy. PLoS ONE 6(2):e16589Google Scholar
  64. Rabinovich M, Huerta R, Varona P, Afraimovich V (2008) Transient cognitive dynamics, metastability, and decision making. PLoS Comput Biol 4(5):e1000072Google Scholar
  65. Raichle M (2010) Two views of brain function. Trends Cogn Sci 14(4):180–190PubMedCrossRefGoogle Scholar
  66. Raichle M, MacLeod A, Snyder A, Powers W, Gusnard D, Shulman G (2001) A default mode of brain function. Proc Natl Acad Sci USA 98(2):676–682PubMedCentralPubMedCrossRefGoogle Scholar
  67. Ritter P, Moosmann M, Villringer A (2009) Rolandic alpha and beta EEG rhythms’ strengths are inversely related to fMRI−BOLD signal in primary somatosensory and motor cortex. Human Brain Mapp 30(4):1168–1187CrossRefGoogle Scholar
  68. Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. NeuroImage 52(3):1059–1069PubMedCrossRefGoogle Scholar
  69. Schultze-Kraft M, Becker R, Breakspear M, Ritter P (2011) Exploiting the potential of three dimensional spatial wavelet analysis to explore nesting of temporal oscillations and spatial variance in simultaneous EEG-fMRI data. Prog Biophys Mol Biol 105(1-2):67–79PubMedCrossRefGoogle Scholar
  70. Smith S, Fox P, Miller K, Glahn D, Fox P, Mackay C, Filippini N, Watkins K, Toro R, Laird A, Beckmann C (2009) Correspondence of the brain’s functional architecture during activation and rest. Proc Natl Acad Sci USA 106(31):13040–13045Google Scholar
  71. Sporns O (2010) Networks of the brain. The MIT Press, Massachusetts Institute of Technology, CambridgeGoogle Scholar
  72. Stam C, Nolte G, Daffertshofer A (2007) Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources. Human Brain Mapp 28(11):1178–1193CrossRefGoogle Scholar
  73. Tass P, Rosenblum M, Weule J, Kurths J, Pikovsky VJ A and, Schnitzler A, Freund HJ (1998) Detection of n:m phase locking from noisy data: application to magnetoencephalography. Phys Rev Lett 81(15):3291–3294CrossRefGoogle Scholar
  74. Van De Ville D, Britz J, Michel C (2010) EEG microstate sequences in healthy humans at rest reveal scale-free dynamics. Proc Natl Acad Sci USA 107(42):18179–18184Google Scholar
  75. Varela F, Lachaux JP, Rodriguez E, Martinerie J (2001) The brainweb: phase synchronization and large-scale integration. Nat Rev Neurosci 2(4):229–239PubMedCrossRefGoogle Scholar
  76. Womelsdorf T, Johnston K, Vinck M, Everling S (2010) Theta-activity in anterior cingulate cortex predicts task rules and their adjustments following errors. Proc Natl Acad Sci USA 107(11):5248–5253PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Saeid Mehrkanoon
    • 1
  • Michael Breakspear
    • 1
    • 2
  • Tjeerd W. Boonstra
    • 1
    • 3
  1. 1.Black Dog InstituteThe University of New South WalesSydneyAustralia
  2. 2.Queensland Institute of Medical ResearchBrisbaneAustralia
  3. 3.Research Institute MOVEVU University Amsterdam AmsterdamThe Netherlands

Personalised recommendations