Neuroscience and Behavioral Physiology

, Volume 49, Issue 9, pp 1135–1144 | Cite as

Functional Organization of the Human Brain in the Resting State

  • A. V. KurganskyEmail author

This review assesses experimental studies of the functioning of the human brain in the resting state. In this state, brain activity has a specific organization in space and time. The spatial (topographical) aspect of this organization consists of the existence of resting state networks, while the temporal organization is apparent as the dynamics of brain electrical activity typical of the resting state. The contributions of studies of the temporospatial organization of brain activity to the overall set of theoretical concepts of the relationships between the structural organization of the brain and its neuronal activity are discussed.


electrophysiology neural mapping resting state networks EEG microstates functional connections 


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  1. Aoki, Y., Ishii, R., Pascual-Marqui, R. D., et al., “Detection of EEG-resting state independent networks by eLORETA-ICA method,” Front. Hum. Neurosci., 9, 31 (2015).PubMedPubMedCentralGoogle Scholar
  2. Atmanspacher, H. and Rotter, S., “Interpreting neurodynamics: concepts and facts,” Cogn. Neurodyn., 2, No. 4, 297–318 (2008).PubMedPubMedCentralGoogle Scholar
  3. Atasoy, S., Donnelly, I., and Pearson, J., “Human brain networks function in connectome-specific harmonic waves,” Nat. Commun., 7, 10340 (2016).PubMedPubMedCentralGoogle Scholar
  4. Bajic, D., Craig, M. M., Borsook, D., and Becerra, L., “Probing intrinsic resting-state networks in the infant rat brain,” Front. Behav. Neurosci., 10, 192 (2016).PubMedPubMedCentralGoogle Scholar
  5. Başar, E. and Güntekin, B., “A review of brain oscillations in cognitive disorders and the role of neurotransmitters,” Brain Res., 1235, 172–193 (2008).Google Scholar
  6. Beckmann, C. F., DeLuca, M., Devlin, J. T., and Smith, S. M., “Investigations into resting-state connectivity using independent component analysis,” Philos. Trans. R. Soc. Lond. B Biol. Sci., 360, No. 1457, 1001–1013 (2005).PubMedCentralGoogle Scholar
  7. Betzel, R. F., Erickson, M. A., Abell, M., et al., “Synchronization dynamics and evidence for a repertoire of network states in resting EEG,” Front. Comput. Neurosci., 6, 74 (2012).PubMedPubMedCentralGoogle Scholar
  8. Biswal, B., Yetkin, F. Z., Haughton, V. M., and Hyde, J. S., “Functional connectivity in the motor cortex of resting human brain using echo-planar MRI,” Magn. Reson. Med., 34, No. 4, 537–541 (1995).PubMedGoogle Scholar
  9. Blaxter, M., “Nematodes: the worm and its relatives,” PLoS Biol., 9, No. 4, e1001050 (2011).PubMedCentralGoogle Scholar
  10. Boly, M., Phillips, C., Tshibanda, L., et al., “Intrinsic brain activity in altered states of consciousness: how conscious is the default mode of brain function?” Ann. NY Acad. Sci., 1129, 119–129 (2008).PubMedGoogle Scholar
  11. Bowyer, S. M., “Coherence a measure of the brain networks: past and present,” Neuropsych. Electrophysiol., 2, 1 (2016).Google Scholar
  12. Bressler, S. L. and Menon, V., “Large-scale brain networks in cognition: emerging methods and principles,” Trends Cogn. Sci., 14, No. 6, 277–290 (2010).Google Scholar
  13. Britz, J., Díaz Hernández, L., Ro, T., and Michel, C. M., “EEG-microstate dependent emergence of perceptual awareness,” Front. Behav. Neurosci., 8, 163 (2014).PubMedCentralGoogle Scholar
  14. Brookes, M. J., Hale, J. R., Zumer, J. M., et al., “Measuring functional connectivity using MEG: methodology and comparison with fcMRI,” Neuroimage, 56, No. 3, 1082–1104 (2011).PubMedPubMedCentralGoogle Scholar
  15. Bullmore, E. T. and Bassett, D. S., “Brain graphs: graphical models of the human brain connectome,” Annu. Rev. Clin. Psychol., 7, 113–140 (2011).PubMedGoogle Scholar
  16. Bullmore, E. and Sporns, O., “The economy of brain network organization,” Nat. Rev. Neurosci., 13, No. 5, 336–349 (2012).Google Scholar
  17. Buzsáki, G., Anastassiou, C. A., and Koch, C., “The origin of extracellular fields and currents-EEG, ECoG, LFP and spikes,” Nat. Rev. Neurosci., 13, No. 6, 407–420 (2012).PubMedCentralGoogle Scholar
  18. Buzsáki, G., Logothetis, N., and Singer, W., “Scaling brain size, keeping timing: evolutionary preservation of brain rhythms,” Neuron, 80, No. 3, 751–764 (2013).PubMedPubMedCentralGoogle Scholar
  19. Casimo, K., Darvas, F., Wander, J., et al., “Regional patterns of cortical phase synchrony in the resting state,” Brain Connect., 6, No. 6, 470–481 (2016).PubMedCentralGoogle Scholar
  20. Chen, T., Cai, W., Ryali, S., et al., “Distinct global brain dynamics and spatiotemporal organization of the salience network,” PLoS Biol., 14, No. 6, e1002469 (2016).PubMedPubMedCentralGoogle Scholar
  21. Chen, A. C., Oathes, D. J., Chang, C., et al., “Causal interactions between fronto-parietal central executive and default-mode networks in humans,” Proc. Natl. Acad. Sci. USA, 110, No. 49, 19944–19949 (2013).PubMedGoogle Scholar
  22. Chialvo, D. R., “Emergent complex neural dynamics,” Nat. Physics, 6, 744–750 (2010).Google Scholar
  23. Colclough, G. L., Woolrich, M. W., Tewarie, P. K., et al., “How reliable are MEG resting-state connectivity metrics?” Neuroimage, 138, 284–293 (2016).PubMedPubMedCentralGoogle Scholar
  24. Congedo, M., John, R. E., De Ridder, D., and Prichep, L., “Group independent component analysis of resting state EEG in large normative samples,” Int. J. Psychophysiol., 78, No. 2, 89–99 (2010).PubMedGoogle Scholar
  25. Coste, C. P., Sadaghiani, S., Friston, K. J., and Kleinschmidt, A., “Ongoing brain activity fluctuations directly account for intertrial and indirectly for intersubject variability in Stroop task performance,” Cereb. Cortex, 21, No. 11, 2612–2619 (2011).PubMedGoogle Scholar
  26. Damoiseaux, J. S., Rombouts, S. A., Barkhof, F., et al., “Consistent resting-state networks across healthy subjects,” Proc. Natl. Acad. Sci. USA, 103, No. 37, 13848–13853 (2006).PubMedGoogle Scholar
  27. de Pasquale, F., Della Penna, S., Snyder, A. Z., et al., “Temporal dynamics of spontaneous MEG activity in brain networks,” Proc. Natl. Acad. Sci. USA, 107, No. 13, 6040–6045 (2010).PubMedGoogle Scholar
  28. de Pasquale, F., Della Penna, S., Snyder, A. Z., et al., “A cortical core for dynamic integration of functional networks in the resting human brain,” Neuron, 74, No. 4, 753–764 (2012).PubMedPubMedCentralGoogle Scholar
  29. Destexhe, A., Hughes, S. W., Rudolph, M., and Crunelli, V., “Are corticothalamic ‘up’ states fragments of wakefulness?” Trends Neurosci., 30, No. 7, 334–342 (2007).PubMedPubMedCentralGoogle Scholar
  30. De Vico Fallani, F., Richiardi, J., Chavez, M., and Achard, S., “Graph analysis of functional brain networks: practical issues in translational neuroscience,” Philos. Trans. R. Soc. Lond. B Biol. Sci., 369, No. 1653 (2014), pii: 20130521.Google Scholar
  31. Eckert, M. A., Kamdar, N. V., Chang, C. E., et al., “A cross-modal system linking primary auditory and visual cortices: evidence from intrinsic fMRI connectivity analysis,” Hum. Brain Mapp., 29, No. 7, 848–857 (2008).PubMedCentralGoogle Scholar
  32. Ewald, A., Marzetti, L., Zappasodi, F., et al., “Estimating true brain connectivity from EEG/MEG data invariant to linear and static transformations in sensor space,” Neuroimage, 60, No. 1, 476–488 (2012).PubMedGoogle Scholar
  33. Fox, M. D., Corbetta, M., Snyder, A. Z., et al., “Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems,” Proc. Natl. Acad. Sci. USA, 103, No. 26, 10046–10051 (2006).PubMedGoogle Scholar
  34. Fox, M. D., Snyder, A. Z., Vincent, J. L., et al., “The human brain is intrinsically organized into dynamic, anticorrelated functional networks,” Proc. Natl. Acad. Sci. USA, 102, No. 27, 9673–9678 (2005).Google Scholar
  35. Fox, M. D. and Raichle, M. E., “Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging,” Nat. Rev. Neurosci., 8, No. 9, 700–711 (2007).PubMedGoogle Scholar
  36. Fransson, P., Skiöld, B., Horsch, S., et al., “Resting-state networks in the infant brain,” Proc. Natl. Acad. Sci. USA, 104, No. 39, 15531–15536 (2007).PubMedGoogle Scholar
  37. Friston, K., “The free-energy principle: a unified brain theory?” Nat. Rev. Neurosci., 11, No. 2, 127–138 (2010).Google Scholar
  38. Friston, K. J., “Functional and effective connectivity: a review,” BrainConnect., 1, No. 1, 13–36 (2011).Google Scholar
  39. Friston, K., “Life as we know it,” J. R. Soc. Interface, 10, No. 86, 20130475 (2013).PubMedCentralGoogle Scholar
  40. Garcés, P., Martín-Buro, M. C., and Maestú, F., “Quantifying the test-retest reliability of magnetoencephalography resting-state functional connectivity,” Brain Connect., 6, No. 6, 448–460 (2016).PubMedGoogle Scholar
  41. Gusnard, D. A., Raichle, M. E., and Raichle, M. E., “Searching for a baseline: functional imaging and the resting human brain,” Nat. Rev. Neurosci., 2, No. 10, 685–694 (2001).PubMedGoogle Scholar
  42. Hall, E. L., Robson, S. E., Morris, P. G., and Brookes, M. J., “The relationship between MEG and fMRI,” Neuroimage, 102, No. 1, 80–91 (2014).PubMedGoogle Scholar
  43. Hari, R. and Parkkonen, L., “The brain timewise: how timing shapes and supports brain function,” Philos. Trans. R. Soc. Lond. B Biol. Sci., 370, No. 1668 (2015), pii: 20140170.Google Scholar
  44. Hassan, M., Dufor, O., Merlet, I., et al., “EEG source connectivity analysis: from dense array recordings to brain networks,” PLoS One, 9, No. 8, e105041 (2014).PubMedPubMedCentralGoogle Scholar
  45. Hipp, J. F. and Siegel, M., “BOLD fMRI correlation reflects frequency-specific neuronal correlation,” Curr. Biol., 25, No. 10, 1368–1374 (2015).PubMedGoogle Scholar
  46. Horn, A., Ostwald, D., Reisert, M., and Blankenburg, F., “The structural-functional connectome and the default mode network of the human brain,” Neuroimage, 102, No. 1, 142–151 (2014).PubMedGoogle Scholar
  47. Jann, K., Kottlow, M., Dierks, T., et al., “Topographic electrophysiological signatures of fMRI resting state networks,” PLoS One, 5, No. 9, e12945 (2010).PubMedPubMedCentralGoogle Scholar
  48. Joel, S. E., Caffo, B. S., van Zijl, P. C., and Pekar, J. J., “On the relationship between seed-based and ICA-based measures of functional connectivity,” Magn. Reson. Med., 66, No. 3, 644–657 (2011).PubMedPubMedCentralGoogle Scholar
  49. Khanna, A., Pascual-Leone, A., Michel, C. M., and Farzan, F., “Microstates in resting-state EEG: current status and future directions,” Neurosci. Biobehav. Rev., 49, 105–113 (2015).PubMedGoogle Scholar
  50. Khanna, A., Pascual-Leone, A., and Farzan, F., “Reliability of resting-state microstate features in electroencephalography,” PLoS One, 9, No. 12, e114163 (2014).PubMedPubMedCentralGoogle Scholar
  51. Kida, T., Tanaka, E., and Kakigi, R., “Multi-dimensional dynamics of human electromagnetic brain activity,” Front. Hum. Neurosci., 9, 713 (2016).PubMedPubMedCentralGoogle Scholar
  52. Koenig, T., Studer, D., Hubl, D., et al., “Brain connectivity at different time-scales measured with EEG,” Philos. Trans. R. Soc. Lond. B Biol. Sci., 360, No. 1457, 1015–1023 (2005).PubMedPubMedCentralGoogle Scholar
  53. Knyazev, G. G., “EEG correlates of self-referential processing,” Front. Hum. Neurosci., 7, 264 (2013).PubMedPubMedCentralGoogle Scholar
  54. Knyazev, G. G., Slobodskoj-Plusnin, J. Y., Bocharov, A. V., and Pylkova, L. V., “The default mode network and EEG α oscillations: an independent component analysis,” Brain Res., 1402, 67–79 (2011).PubMedGoogle Scholar
  55. Kutsarova, E., Munz, M., and Ruthazer, E. S., “Rules for shaping neural connections in the developing brain,” Front. Neural Circuits, 10, 111 (2017).PubMedPubMedCentralGoogle Scholar
  56. Laufs, H., Krakow, K., Sterzer, P., et al., “Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest,” Proc. Natl. Acad. Sci. USA, 100, No. 19, 11053–11058 (2003).PubMedGoogle Scholar
  57. Leighton, A. H. and Lohmann, C., “The wiring of developing sensory circuits – from patterned spontaneous activity to synaptic plasticity mechanisms,” Front. Neural Circuits, 10, 71 (2016).PubMedPubMedCentralGoogle Scholar
  58. Liao, W., Mantini, D., Zhang, Z., et al., “Evaluating the effective connectivity of resting state networks using conditional Granger causality,” Biol. Cybern., 102, No. 1, 57–69 (2010).Google Scholar
  59. Laughlin, S. B. and Sejnowski, T. J., “Communication in neuronal networks,” Science, 301, No. 5641, 1870–1874 (2003).PubMedPubMedCentralGoogle Scholar
  60. Lindquist, M. A., Meng Loh, J., Atlas, L. Y., and Wager, T. D., “Modeling the hemodynamic response function in fMRI: efficiency, bias and mis-modeling,” Neuroimage, 45, No. 1 Supplement, S187–198 (2009).PubMedGoogle Scholar
  61. Lopes da Silva, F., “EEG and MEG: relevance to neuroscience,” Neuron, 80, No. 5, 1112–1128 (2013).PubMedGoogle Scholar
  62. Mantini, D., Della Penna, S., Marzetti, L., et al., “A signal-processing pipeline for magnetoencephalography resting-state networks,” Brain Connect., 1, No. 1, 49–59 (2011).PubMedGoogle Scholar
  63. Mantini, D., Perrucci, M. G., Del Gratta, C., et al., “Electrophysiological signatures of resting state networks in the human brain,” Proc. Natl. Acad. Sci. USA, 104, No. 32, 13170–13175 (2007).PubMedGoogle Scholar
  64. McCormick, D. A., McGinley, M. J., and Salkoff, D. B., “Brain state dependent activity in the cortex and thalamus,” Curr. Opin. Neurobiol., 31, 133–140 (2015).PubMedGoogle Scholar
  65. Menon, V., “Large-Scale functional brain organization,” in: Brain Mapping: An Encyclopedic Reference, Toga, A. W. (ed.), Elsevier, Academic Press (2015), Vol. 2, pp. 449–459.Google Scholar
  66. Menon, V. and Uddin, L. Q., “Saliency, switching, attention and control: a network model of insula function,” Brain Struct. Funct., 214, No. 5–6, 655–667 (2010).PubMedPubMedCentralGoogle Scholar
  67. Miller, K. J., Weaver, K. E., and Ojemann, J. G., “Direct electrophysiological measurement of human default network areas,” Proc. Natl. Acad. Sci. USA, 106, No. 29, 12,174–12,177 (2009).Google Scholar
  68. Mongerson, C. R. L., Jennings, R. W., Borsook, D., et al., “Resting-state functional connectivity in the infant brain: methods, pitfalls, and potentiality,” Front. Pediatr., 5, 159 (2017).PubMedPubMedCentralGoogle Scholar
  69. Morcom, A. M. and Fletcher, P. C., “Does the brain have a baseline? Why we should be resisting a rest,” NeuroImage, 37, 1073–1082 (2007).PubMedGoogle Scholar
  70. Mountcastle, V. B., “The view from within: pathways to the study of perception,” Johns Hopkins Med. J., 136, No. 3, 109–131 (1975).PubMedGoogle Scholar
  71. Neske, G. T., “The slow oscillation in cortical and thalamic networks: mechanisms and functions,” Front. Neural Circuits, 9, 88 (2016).PubMedPubMedCentralGoogle Scholar
  72. Nolte, G., Bai, U., Weathon, L., et al., “Identifying true brain interaction from EEG data using the imaginary part of coherency,” Clin. Neurophysiol., 115, 2294–2307 (2004).Google Scholar
  73. Papo, D., “Why should cognitive neuroscientists study the brain’s resting state?” Front. Hum. Neurosci., 7, 45 (2013).PubMedPubMedCentralGoogle Scholar
  74. Pascual-Marqui, R. D., “Standardized low-resolution brain electromagnetic tomography (sLORETA, technical details,” Methods Find. Exp. Clin. Pharmacol., 24, Suppl. D, 5–12 (2002).Google Scholar
  75. Pascual-Marqui, R. D., Michel, C. M., and Lehmann, D., “Segmentation of brain electrical activity into microstates: model estimation and validation,” IEEE Trans. Biomed. Eng., 42, No. 7, 658–665 (1995).PubMedGoogle Scholar
  76. Raichle, M. E., “The restless brain: how intrinsic activity organizes brain function,” Philos. Trans. R. Soc. Lond. B Biol. Sci., 370, No. 1668 (2015), pii: 20140172.Google Scholar
  77. Raichle, M. E., MacLeod, A. M., Snyder, A. Z., et al., “A default mode of brain function,” Proc. Natl. Acad. Sci. USA, 98, No. 2, 676–682 (2001).Google Scholar
  78. Raichle, M. E. and Snyder, A. Z., “A default mode of brain function: a brief history of an evolving idea,” Neuroimage, 37, No. 4, 1083–1090; discussion, 1097–1099 (2007).Google Scholar
  79. Scheeringa, R., Bastiaansen, M. C., Petersson, K. M., et al., “Frontal theta EEG activity correlates negatively with the default mode network in resting state,” Int. J. Psychophysiol., 67, No. 3, 242–251 (2008).PubMedGoogle Scholar
  80. Schoffelen, J. M. and Gross, J., “Source connectivity analysis with MEG and EEG,” Hum. Brain Mapp., 30, No. 6, 1857–1865 (2009).PubMedGoogle Scholar
  81. Seeley, W. W., Menon, V., Schatzberg, A. F., et al., “Dissociable intrinsic connectivity networks for salience processing and executive control,” J. Neurosci., 27, No. 9, 2349–2356 (2007).PubMedCentralGoogle Scholar
  82. Siems, M., Pape, A. A., Hipp, J. F., and Siegel, M., “Measuring the cortical correlation structure of spontaneous oscillatory activity with EEG and MEG,” Neuroimage, 129, 345–355 (2016).Google Scholar
  83. Smith, S. M., Fox, P. T., Miller, K. L., et al., “Correspondence of the brain’s functional architecture during activation and rest,” Proc. Natl. Acad. Sci. USA, 106, No. 31, 13040–13045 (2009).Google Scholar
  84. Sporns, O., “The human connectome: origins and challenges,” Neuroimage, 80, 53–61 (2013).PubMedGoogle Scholar
  85. Sporns, O., Tononi, G., and Kötter, R., “The human connectome: A structural description of the human brain,” PLoS Comput. Biol., 1, No. 4, e42 (2005).PubMedPubMedCentralGoogle Scholar
  86. Srinivasan, R., Winter, W. R., Ding, J., and Nunez, P. L., “EEG and MEG coherence: measures of functional connectivity at distinct spatial scales of neocortical dynamics,” J. Neurosci. Meth ., 166, No. 1, 41–52 (2007).PubMedPubMedCentralGoogle Scholar
  87. Srinivasan, R., Winter, W. R., and Nunez, P. L., “Source analysis of EEG oscillations using high-resolution EEG and MEG,” Prog. Brain Res., 159, 29–42 (2006).PubMedPubMedCentralGoogle Scholar
  88. Stam, C. J., “Nonlinear dynamical analysis of EEG and MEG: review of an emerging field,” Clin. Neurophysiol., 116, No. 10, 2266–2301 (2005).PubMedGoogle Scholar
  89. Stam, C. J., Nolte, G., and Daffertshofer, A., “Phase lag index: assessment of functional connectivity from multichannel EEG and MEG with diminished bias from common sources,” Hum. Brain Mapp., 28, No. 11, 1178–1193 (2007).PubMedGoogle Scholar
  90. Thatcher, R. W., North, D., and Biver, C., “EEG and intelligence: relations between EEG coherence, EEG phase delay and power,” Clin. Neurophysiol., 116, No. 9, 2129–2141 (2005).PubMedGoogle Scholar
  91. Thatcher, R. W., North, D. M., and Biver, C. J., “Development of cortical connections as measured by EEG coherence and phase delays,” Hum. Brain Mapp., 29, No. 12, 1400–1415 (2008).PubMedGoogle Scholar
  92. Tomasi, D., Wang, G. J., and Volkow, N. D., “Energetic cost of brain functional connectivity,” Proc. Natl. Acad. Sci. USA, 110, No. 33, 13642–13647 (2013).PubMedGoogle Scholar
  93. van den Heuvel, M. P., Mandl, R. C., Kahn, R. S., and Hulshoff Pol, H. E., “Functionally linked resting-state networks reflect the underlying structural connectivity architecture of the human brain,” Hum. Brain Mapp., 30, No. 10, 3127–3141 (2009).PubMedGoogle Scholar
  94. Wens, V., Bourguignon, M., Goldman, S., et al., “Inter-and intra-subject variability of neuromagnetic resting state networks,” Brain Topogr., 27, No. 5, 620–634 (2014).PubMedGoogle Scholar
  95. Werner, G., “Fractals in the nervous system: conceptual implications for theoretical neuroscience,” Front. Physiol., 1, 15 (2010).PubMedPubMedCentralGoogle Scholar
  96. White, J. G., Southgate, E., Thomson, J. N., and Brenner, S., “The structure of the nervous system of the nematode Caenorhabditis elegans,” Philos. Trans. R. Soc. Lond. B Biol. Sci., 314, No. 1165, 1–340 (1986).PubMedGoogle Scholar
  97. Yaple, Z., “A contemporary and interdisciplinary definition of the self,” Psychol. J. High. School Econ., 12, No. 4, 7–12 (2015).Google Scholar

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Authors and Affiliations

  1. 1.Institute of Age Physiology, Russian Academy of EducationMoscowRussia

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