Advertisement

MEG Studies on the Connectivity of Brain Networks in Children

  • Blake W. JohnsonEmail author
  • Wei HeEmail author
Reference work entry

Abstract

In recent years MEG has been well established as a method for investigating neuronal connectivity of human brain networks. In this chapter we consider the application of network MEG methods to the studies of the developing brain. We begin with an overview of methodological challenges of pediatric MEG, consider a key problem presented by the small and variable head geometries of children, and discuss methods and ancillary technologies that have aided our own research using a dedicated pediatric MEG scanner. We then turn to our MEG research on the development of neuronal oscillations, the resting-state network, and face processing, with a focus on functional connectivity and network analyses. We aim to provide an accessible introduction to, and motivating evidence for, using MEG to study normative and nonnormative brain development from a network perspective.

Keywords

Child, Development+ Dynamic causal modeling (DCM) Face perception Graph theory M170 N170 Magnetoencephalography (MEG) Mock scanner MST Network Oscillations Pediatric Resting-state 

References

  1. Almli CR, Rivkin MJ, McKinstry RC (2007) The NIH MRI study of normal brain development (Objective-2): Newborns, infants, toddlers, and preschoolers. NeuroImage 35(1):308–325. https://doi.org/10.1016/j.neuroimage.2006.08.058CrossRefPubMedGoogle Scholar
  2. Baillet S (2017) Magnetoencephalography for brain electrophysiology and imaging. Nat Neurosci 20(3):327–339. https://doi.org/10.1038/nn.4504CrossRefPubMedPubMedCentralGoogle Scholar
  3. Barabasi AL, Albert R (1999) Emergence of scaling in random networks. Science 286(5439):509–512CrossRefGoogle Scholar
  4. Barnes JJ, Woolrich MW, Baker K, Colclough GL, Astle DE (2016) Electrophysiological measures of resting state functional connectivity and their relationship with working memory capacity in childhood. Dev Sci 19(1):19–31. https://doi.org/10.1111/desc.12297CrossRefPubMedGoogle Scholar
  5. Barry RJ, Clarke AR, McCarthy R, Selikowitz M, Johnstone SJ, Rushby JA (2004) Age and gender effects in EEG coherence: I. Developmental trends in normal children. Clin Neurophysiol 115(10):2252–2258. https://doi.org/10.1016/j.clinph.2004.05.004CrossRefPubMedGoogle Scholar
  6. Batty M, Taylor MJ (2006) The development of emotional face processing during childhood. Dev Sci 9(2):207–220. https://doi.org/10.1111/j.1467-7687.2006.00480.xCrossRefPubMedGoogle Scholar
  7. Benes FM, Turtle M, Khan Y, Farol P (1994) Myelination of a key relay zone in the hippocampal formation occurs in the human brain during childhood, adolescence, and adulthood. Arch Gen Psychiatry 51(6):477–484CrossRefGoogle Scholar
  8. Bentin S, Allison T, Puce A, Perez E, McCarthy G (1996) Electrophysiological Studies of Face Perception in Humans. J Cogn Neurosci 8(6):551–565. https://doi.org/10.1162/jocn.1996.8.6.551CrossRefPubMedPubMedCentralGoogle Scholar
  9. Boersma M, Smit DJ, de Bie HM, Van Baal GC, Boomsma DI, de Geus EJ, Delemarre-van de Waal HA, Stam CJ (2011) Network analysis of resting state EEG in the developing young brain: structure comes with maturation. Hum Brain Mapp 32(3):413–425. https://doi.org/10.1002/hbm.21030CrossRefPubMedGoogle Scholar
  10. Boersma M, Smit DJ, Boomsma DI, De Geus EJ, Delemarre-van de Waal HA, Stam CJ (2013) Growing trees in child brains: graph theoretical analysis of electroencephalography-derived minimum spanning tree in 5- and 7-year-old children reflects brain maturation. Brain Connect 3(1):50–60. https://doi.org/10.1089/brain.2012.0106CrossRefPubMedGoogle Scholar
  11. Brookes MJ, Hale JR, Zumer JM, Stevenson CM, Francis ST, Barnes GR, Nagarajan SS (2011) Measuring functional connectivity using MEG: methodology and comparison with fcMRI. NeuroImage 56(3):1082–1104. https://doi.org/10.1016/j.neuroimage.2011.02.054CrossRefPubMedPubMedCentralGoogle Scholar
  12. Brown TT, Jernigan TL (2012) Brain development during the preschool years. Neuropsychol Rev 22(4):313–333. https://doi.org/10.1007/s11065-012-9214-1CrossRefPubMedPubMedCentralGoogle Scholar
  13. Buzsaki G (2002) Theta oscillations in the hippocampus. Neuron 33(3):325–340CrossRefGoogle Scholar
  14. Buzsaki G (2006) Rhythms of the brain. Oxford University Press, OxfordCrossRefGoogle Scholar
  15. Buzsaki G, Draguhn A (2004) Neuronal oscillations in cortical networks. Science 304(5679):1926–1929. https://doi.org/10.1126/science.1099745CrossRefGoogle Scholar
  16. Cao M, Wang JH, Dai ZJ, Cao XY, Jiang LL, Fan FM, Song XW, Xia MR, Shu N, Dong Q, Milham MP, Castellanos FX, Zuo XN, He Y (2014) Topological organization of the human brain functional connectome across the lifespan. Dev Cogn Neurosci 7:76–93. https://doi.org/10.1016/j.dcn.2013.11.004CrossRefPubMedGoogle Scholar
  17. Cao M, Huang H, He Y (2017) Developmental connectomics from infancy through early childhood. Trends Neurosci 40(8):494–506. https://doi.org/10.1016/j.tins.2017.06.003CrossRefPubMedPubMedCentralGoogle Scholar
  18. Carey S, Diamond R (1977) From piecemeal to configurational representation of faces. Science 195(4275):312–314CrossRefGoogle Scholar
  19. Cheyne D, Jobst C, Tesan G, Crain S, Johnson B (2014) Movement-related neuromagnetic fields in preschool age children. Hum Brain Mapp 35(9):4858–4875. https://doi.org/10.1002/hbm.22518CrossRefPubMedPubMedCentralGoogle Scholar
  20. Ciesielski KR, Stephen JM (2014) Pediatric MEG: investigating spatio-temporal connectivity of developing networks. In: Supek S, Aine CJ (eds) Magnetoencephalography: from signals to dynamic cortical networks. Springer, New York, pp 525–555Google Scholar
  21. Clayton MS, Yeung N, Cohen Kadosh R (2017) The many characters of visual alpha oscillations. European J Neurosci. https://doi.org/10.1111/ejn.13747CrossRefGoogle Scholar
  22. Cragg L, Kovacevic N, McIntosh AR, Poulsen C, Martinu K, Leonard G, Paus T (2011) Maturation of EEG power spectra in early adolescence: a longitudinal study. Dev Sci 14(5):935–943. https://doi.org/10.1111/j.1467-7687.2010.01031.xCrossRefPubMedGoogle Scholar
  23. Crookes K, McKone E (2009) Early maturity of face recognition: no childhood development of holistic processing, novel face encoding, or face-space. Cognition 111(2):219–247. https://doi.org/10.1016/j.cognition.2009.02.004CrossRefPubMedGoogle Scholar
  24. de Bie HMA, Boersma M, Wattjesm MP, Adriaansem S, Vermeulenm RJ, Oostromm KJ, Huisman J, Veltman DJ, Delemarre-Van de Waal HA (2010) Preparing children with a mock scanner training protocol results in high quality structural and functional MRI scans. European J Pediatr 169:1079–1085CrossRefGoogle Scholar
  25. de Haan M, Pascalis O, Johnson MH (2002) Specialization of neural mechanisms underlying face recognition in human infants. J Cogn Neurosci 14(2):199–209. https://doi.org/10.1162/089892902317236849CrossRefPubMedGoogle Scholar
  26. de Haan M, Johnson MH, Halit H (2003) Development of face-sensitive event-related potentials during infancy: a review. Int J Psychophysiol 51(1):45–58CrossRefGoogle Scholar
  27. de Heering A, Houthuys S, Rossion B (2007) Holistic face processing is mature at 4 years of age: evidence from the composite face effect. J Exp Child Psychol 96(1):57–70. https://doi.org/10.1016/j.jecp.2006.07.001CrossRefPubMedGoogle Scholar
  28. Deffke I, Sander T, Heidenreich J, Sommer W, Curio G, Trahms L, Lueschow A (2007) MEG/EEG sources of the 170-ms response to faces are co-localized in the fusiform gyrus. NeuroImage 35(4):1495–1501. https://doi.org/10.1016/j.neuroimage.2007.01.034CrossRefPubMedGoogle Scholar
  29. Dementieva YA, Vance DD, Donnelly SL, Elston LA, Wolpert CM, Ravan SA, DeLong GR, Abramson RK, Wright HH, Cuccaro ML (2005) Accelerated head growth in early development of individuals with autism. Pediatr Neurol 32(2):102–108. https://doi.org/10.1016/j.pediatrneurol.2004.08.005CrossRefPubMedGoogle Scholar
  30. Etchell AC, Ryan M, Martin E, Johnson BW, Sowman PF (2016) Abnormal low beta modulation in non-fluent preschool children: A magnetoencephalographic study of rhythm tracking. NeuroImage 125:953–963. https://doi.org/10.1016/j.neuroimage.2015.10.086CrossRefGoogle Scholar
  31. Fair DA, Cohen AL, Power JD, Dosenbach NU, Church JA, Miezin FM, Petersen SE (2009) Functional brain networks develop from a “local to distributed” organization. PLoS Comput Biol 5(5):e1000381. https://doi.org/10.1371/journal.pcbi.1000381CrossRefPubMedPubMedCentralGoogle Scholar
  32. Friston KJ (1994) Functional and effective connectivity in neuroimaging: a synthesis. Hum Brain Mapp 2(1–2):56–78. https://doi.org/10.1002/hbm.460020107CrossRefGoogle Scholar
  33. Friston KJ, Harrison L, Penny W (2003) Dynamic causal modelling. NeuroImage 19(4):1273–1302. S1053811903002027CrossRefGoogle Scholar
  34. Friston KJ, Ashburner JT, Kiebel SJ, Nichols TE, Penny WD (2011) Statistical parametric mapping: the analysis of functional brain images. Academic, CambridgeGoogle Scholar
  35. Gaetz W, Otsubo H, Pang EW (2008) Magnetoencephalography for clinical pediatrics: the effect of head positioning on measurement of somatosensory-evoked fields. Clin Neurophysiol 119(8):1923–1933. https://doi.org/10.1016/j.clinph.2008.04.291CrossRefPubMedGoogle Scholar
  36. Gaetz W, Gordon R, Papadelis C, Fujiwara H, Rose D, Edgar J, Schwartz E, Roberts T (2015) Magnetoencephalography for clinical pediatrics: recent advances in hardware, methods, and clinical applications. J Pediatr Epilepsy 04(04):139–155. https://doi.org/10.1055/s-0035-1563726CrossRefGoogle Scholar
  37. Gao W, Gilmore JH, Giovanello KS, Smith JK, Shen D, Zhu H, Lin W (2011) Temporal and spatial evolution of brain network topology during the first two years of life. PLoS One 6(9):e25278. https://doi.org/10.1371/journal.pone.0025278CrossRefPubMedPubMedCentralGoogle Scholar
  38. Ge L, Anzures G, Wang Z, Kelly DJ, Pascalis O, Quinn PC, Lee K (2008) An inner face advantage in children’s recognition of familiar peers. J Exp Child Psych 101(2):124–136. https://doi.org/10.1016/j.jecp.2008.05.006CrossRefGoogle Scholar
  39. Gomez CM, Rodriguez-Martinez EI, Fernandez A, Maestu F, Poza J, Gomez C (2017) Absolute power spectral density changes in the magnetoencephalographic activity during the transition from childhood to adulthood. Brain Topogr 30(1):87–97. https://doi.org/10.1007/s10548-016-0532-0CrossRefPubMedGoogle Scholar
  40. Grayson DS, Fair DA (2017) Development of large-scale functional networks from birth to adulthood: a guide to the neuroimaging literature. NeuroImage 160:15–31. https://doi.org/10.1016/j.neuroimage.2017.01.079CrossRefPubMedPubMedCentralGoogle Scholar
  41. Grayson DS, Ray S, Carpenter S, Iyer S, Dias TG, Stevens C, Nigg JT, Fair DA (2014) Structural and functional rich club organization of the brain in children and adults. PLoS One 9(2):e88297. https://doi.org/10.1371/journal.pone.0088297CrossRefPubMedPubMedCentralGoogle Scholar
  42. Gu S, Satterthwaite TD, Medaglia JD, Yang M, Gur RE, Gur RC, Bassett DS (2015) Emergence of system roles in normative neurodevelopment. Proc Nat Acad Sci USA 112(44):13,681–13,686. https://doi.org/10.1073/pnas.1502829112CrossRefGoogle Scholar
  43. Halit H, de Haan M, Johnson MH (2003) Cortical specialisation for face processing: face-sensitive event-related potential components in 3- and 12-month-old infants. NeuroImage 19(3):1180–1193CrossRefGoogle Scholar
  44. He W, Johnson BW (2018) Development of face recognition: dynamic causal modelling of MEG data. Dev Cogn Neurosci 30:13–22. https://doi.org/10.1016/j.dcn.2017.11.010CrossRefPubMedGoogle Scholar
  45. He W, Brock J, Johnson BW (2014) Face-sensitive brain responses measured from a four-year-old child with a custom-sized child MEG system. J Neurosci Methods 222:213–217. https://doi.org/10.1016/j.jneumeth.2013.11.020CrossRefPubMedGoogle Scholar
  46. He W, Brock J, Johnson BW (2015) Face processing in the brains of pre-school aged children measured with MEG. NeuroImage 106:317–327. https://doi.org/10.1016/j.neuroimage.2014.11.029CrossRefPubMedPubMedCentralGoogle Scholar
  47. Heinrichs-Graham E, McDermott TJ, Mills MS, Wiesman AI, Wang YP, Stephen JM, Calhoun VD, Wilson TW (2018) The lifespan trajectory of neural oscillatory activity in the motor system. Dev Cogn Neurosci 30:159–168. https://doi.org/10.1016/j.dcn.2018.02.013CrossRefPubMedPubMedCentralGoogle Scholar
  48. Hillebrand A, Barnes GR, Bosboom JL, Berendse HW, Stam CJ (2012) Frequency-dependent functional connectivity within resting-state networks: an atlas-based MEG beamformer solution. NeuroImage 59(4):3909–3921. https://doi.org/10.1016/j.neuroimage.2011.11.005CrossRefPubMedPubMedCentralGoogle Scholar
  49. Hinton VJ (2002) Ethics of neuroimaging in pediatric development. Brain Cogn 50(3):455–468CrossRefGoogle Scholar
  50. Hoffman EA, Haxby JV (2000) Distinct representations of eye gaze and identity in the distributed human neural system for face perception. Nat Neurosci 3(1):80–84. https://doi.org/10.1038/71152CrossRefPubMedGoogle Scholar
  51. Horwitz B, Amunts K, Bhattacharyya R, Patkin D, Jeffries K, Zilles K, Braun AR (2003) Activation of Broca’s area during the production of spoken and signed language: a combined cytoarchitectonic mapping and PET analysis. Neuropsychologia 41(14):1868–1876CrossRefGoogle Scholar
  52. Huttenlocher PR, Dabholkar AS (1997) Regional differences in synaptogenesis in human cerebral cortex. J Comp Neurol 387(2):167–178CrossRefGoogle Scholar
  53. Hwang K, Hallquist MN, Luna B (2013) The development of hub architecture in the human functional brain network. Cereb Cortex 23(10):2380–2393. https://doi.org/10.1093/cercor/bhs227CrossRefPubMedGoogle Scholar
  54. Irimia A, Erhart MJ, Brown TT (2014) Variability of magnetoencephalographic sensor sensitivity measures as a function of age, brain volume and cortical area. Clin Neurophysiol 125(10):1973–1984. https://doi.org/10.1016/j.clinph.2014.01.027CrossRefPubMedPubMedCentralGoogle Scholar
  55. Jeffery L, Rhodes G (2011) Insights into the development of face recognition mechanisms revealed by face aftereffects. Brit J Psychol 102(4):799–815. https://doi.org/10.1111/j.2044-8295.2011.02066.xCrossRefPubMedGoogle Scholar
  56. Jenkinson N, Brown P (2011) New insights into the relationship between dopamine, beta oscillations and motor function. Trend Neurosci 34(12):611–618. https://doi.org/10.1016/j.tins.2011.09.003CrossRefPubMedGoogle Scholar
  57. Johnson BW, Crain S, Thornton R, Tesan G, Reid M (2010) Measurement of brain function in pre-school children using a custom sized whole-head MEG sensor array. Clin Neurophysiol 121(3):340–349. https://doi.org/10.1016/j.clinph.2009.10.017CrossRefPubMedPubMedCentralGoogle Scholar
  58. Kanwisher N, Yovel G (2006) The fusiform face area: a cortical region specialized for the perception of faces. Phil Trans R Soc Lond Series B Biol Sci 361(1476):2109–2128. X83871K50X365124. https://doi.org/10.1098/rstb.2006.1934CrossRefGoogle Scholar
  59. Khan JJ, Donnelly LF, Koch BL, Curtwright LA, Dickerson JM, Hardin JL, Hutchinson S, Wright J, Gessner KE (2007) A program to decrease the need for pediatric sedation for CT and MRI. Appl Radiol 2007:30–33Google Scholar
  60. Kim DH, Noh JD, Jeong H (2004) Scale-free trees: the skeletons of complex networks. Phys Rev E Stat Nonlin Soft Matter Phys 70(4 Pt 2):046126. https://doi.org/10.1103/PhysRevE.70.046126CrossRefPubMedGoogle Scholar
  61. Kimura I, Kubota M, Hirose H, Yumoto M, Sakakihara Y (2004) Children are sensitive to averted eyes at the earliest stage of gaze processing. NeuroReport 15(8):1345–1348. https://doi.org/10.1097/01.wnr.0000129574.43925.59CrossRefPubMedGoogle Scholar
  62. Klimesch W (1999) EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res Brain Res Rev. 29(2–3):169–195CrossRefGoogle Scholar
  63. Knappe S, Sander T, Trahms L (2014) Optically-pumped magnetometers for MEG. In: Supek S, Aine CJ (eds) Magnetoencephalography: from signals to dynamic cortical networks. Springer, New York, pp 993–999Google Scholar
  64. Kuefner D, de Heering A, Jacques C, Palmero-Soler E, Rossion B (2010) Early visually evoked electrophysiological responses over the human brain (P1, N170) show stable patterns of face-sensitivity from 4 years to adulthood. Front Hum Neurosci 3:67. https://doi.org/10.3389/neuro.09.067.2009CrossRefPubMedPubMedCentralGoogle Scholar
  65. Kylliainen A, Braeutigam S, Hietanen JK, Swithenby SJ, Bailey AJ (2006a) Face- and gaze-sensitive neural responses in children with autism: a magnetoencephalographic study. Eur J Neurosci 24(9):2679–2690. https://doi.org/10.1111/j.1460-9568.2006.05132.xCrossRefPubMedGoogle Scholar
  66. Kylliainen A, Braeutigam S, Hietanen JK, Swithenby SJ, Bailey AJ (2006b) Face and gaze processing in normally developing children: a magnetoencephalographic study. Europ J Neurosci 23(3):801–810. https://doi.org/10.1111/j.1460-9568.2005.04554.xCrossRefGoogle Scholar
  67. Larson E, Taulu S (2017) The importance of properly compensation for head movements during MEG acquisition across different age groups. Brain Topogr 30:172–181CrossRefGoogle Scholar
  68. Lew S, Sliva DD, Choe MS, Grant PE, Okada Y, Wolters CH, Hamalainen MS (2013) Effects of sutures and fontanels on MEG and EEG source analysis in a realistic infant head model. NeuroImage 76:282–293. https://doi.org/10.1016/j.neuroimage.2013.03.017CrossRefPubMedPubMedCentralGoogle Scholar
  69. Linkenkaer-Hansen K, Palva JM, Sams M, Hietanen JK, Aronen HJ, Ilmoniemi RJ (1998) Face-selective processing in human extrastriate cortex around 120 ms after stimulus onset revealed by magneto- and electroencephalography. Neurosci Lett 253(3):147–150CrossRefGoogle Scholar
  70. Liu J, Harris A, Kanwisher N (2010) Perception of face parts and face configurations: an FMRI study. J Cogn Neurosci 22(1):203–211. https://doi.org/10.1162/jocn.2009.21203CrossRefPubMedPubMedCentralGoogle Scholar
  71. Lochy A, Van Reybroeck M, Rossion B (2016) Left cortical specialization for visual letter strings predicts rudimentary knowledge of letter-sound association in preschoolers. Proc Nat Acad Sci USA 113(30):8544–8549. https://doi.org/10.1073/pnas.1520366113CrossRefPubMedGoogle Scholar
  72. Lundqvist M, Herman P, Lansner A (2013) Effect of prestimulus alpha power, phase, and synchronization on stimulus detection rates in a biophysical attractor network model. J Neurosci 33(29):11,817–11,824. https://doi.org/10.1523/JNEUROSCI.5155-12.2013CrossRefGoogle Scholar
  73. Marcuse LV, Schneider M, Mortati KA, Donnelly KM, Arnedo V, Grant AC (2008) Quantitative analysis of the EEG posterior-dominant rhythm in healthy adolescents. Clin Neurophysiol 119(8):1778–1781. https://doi.org/10.1016/j.clinph.2008.02.023CrossRefPubMedGoogle Scholar
  74. Menon V (2013) Developmental pathways to functional brain networks: Emerging principles. Trend Cog Sci 17(12):627–640. https://doi.org/10.1016/j.tics.2013.09.015CrossRefGoogle Scholar
  75. Mierau A, Felsch M, Hulsdunker T, Mierau J, Bullermann P, Weiss B, Struder HK (2016) The interrelation between sensorimotor abilities, cognitive performance and individual EEG alpha peak frequency in young children. Clin Neurophysiol 127(1):270–276. https://doi.org/10.1016/j.clinph.2015.03.008CrossRefPubMedGoogle Scholar
  76. Miller DJ, Duka T, Stimpson CD, Schapiro SJ, Baze WB, McArthur MJ, Fobbs AJ, Sousa AM, Sestan N, Wildman DE, Lipovich L, Kuzawa CW, Hof PR, Sherwood CC (2012) Prolonged myelination in human neocortical evolution. Proc Nat Acad Sci USA 109(41):16,480–16,485. https://doi.org/10.1073/pnas.1117943109CrossRefGoogle Scholar
  77. Miskovic V, Ma X, Chou CA, Fan M, Owens M, Sayama H, Gibb BE (2015) Developmental changes in spontaneous electrocortical activity and network organization from early to late childhood. NeuroImage 118:237–247. https://doi.org/10.1016/j.neuroimage.2015.06.013CrossRefPubMedPubMedCentralGoogle Scholar
  78. Mondloch CJ, Le Grand R, Maurer D (2002) Configural face processing develops more slowly than featural face processing. Perception 31(5):553–566CrossRefGoogle Scholar
  79. Newman, MEJ (2010) Networks. An introduction. Oxford University Press, OxfordGoogle Scholar
  80. O’Neill GC, Tewarie PK, Colclough GL, Gascoyne LE, Hunt BAE, Morris PG, Woolrich MW, Brookes MJ (2017) Measurement of dynamic task related functional networks using MEG. NeuroImage 146:667–678. https://doi.org/10.1016/j.neuroimage.2016.08.061CrossRefPubMedPubMedCentralGoogle Scholar
  81. Okada Y, Hamalainen M, Pratt K, Mascarenas A, Miller P, Han M, Robles J, Cavallini A, Power B, Sieng K, Sun L, Lew S, Doshi C, Ahtam B, Dinh C, Esch L, Grant E, Nummenmaa A, Paulson D (2016) BabyMEG: A whole-head pediatric magnetoencephalography system for human brain development research. Rev Sci Instr 87(9):094301. https://doi.org/10.1063/1.4962020CrossRefGoogle Scholar
  82. Pang EW (2011) Practical aspects of running developmental studies in the MEG. Brain Topogr 24(3–4):253–260. https://doi.org/10.1007/s10548-011-0175-0CrossRefPubMedPubMedCentralGoogle Scholar
  83. Panzeri S, Macke JH, Gross J, Kayser C (2015) Neural population coding: Combining insights from microscopic and mass signals. Trend Cog Sci 19(3):162–172. https://doi.org/10.1016/j.tics.2015.01.002CrossRefGoogle Scholar
  84. Poldrack RA (2010) Interpreting developmental changes in neuroimaging signals. Hum Brain Mapp 31(6):872–878. https://doi.org/10.1002/hbm.21039CrossRefPubMedGoogle Scholar
  85. Puligheddu M, de Munck JC, Stam CJ, Verbunt J, de Jongh A, van Dijk BW, Marrosu F (2005) Age distribution of MEG spontaneous theta activity in healthy subjects. Brain Topogr 17(3):165–175CrossRefGoogle Scholar
  86. Raschle N, Zuk J, Ortiz-Mantilla S, Sliva DD, Franceschi A, Grant PE, Benasich AA, Gaab N (2012) Pediatric neuroimaging in early childhood and infancy: challenges and practical guidelines. Ann NY Acad Sci 1252:43–50. https://doi.org/10.1111/j.1749-6632.2012.06457.xCrossRefPubMedGoogle Scholar
  87. Roberts TP, Paulson DN, Hirschkoff E, Pratt K, Mascarenas A, Miller P, Han M, Caffrey J, Kincade C, Power B, Murray R, Chow V, Fisk C, Ku M, Chudnovskaya D, Dell J, Golembski R, Lam P, Blaskey L, Kuschner E, Bloy L, Gaetz W, Edgar JC (2014) Artemis 123: development of a whole-head infant and young child MEG system. Front Hum Neurosci 8:99. https://doi.org/10.3389/fnhum.2014.00099CrossRefPubMedPubMedCentralGoogle Scholar
  88. Roche A, Mukherjee D, Guo S, Moore W (1987) Head circumference reference data: birth to 18 years. Pediatr 79:706–712Google Scholar
  89. Rodriguez-Martinez EI, Ruiz-Martinez FJ, Barriga Paulino CI, Gomez CM (2017) Frequency shift in topography of spontaneous brain rhythms from childhood to adulthood. Cog Neurodyn 11(1):23–33. https://doi.org/10.1007/s11571-016-9402-4CrossRefGoogle Scholar
  90. Rollins J, Collins J, Holden K (2010) United States head circumference growth reference charts: birth to 21 years. J Pediatr 156(6):907–913CrossRefGoogle Scholar
  91. Rossion B, Caharel S (2011) ERP evidence for the speed of face categorization in the human brain: disentangling the contribution of low-level visual cues from face perception. Vis Res 51(12):1297–1311. https://doi.org/10.1016/j.visres.2011.04.003CrossRefPubMedGoogle Scholar
  92. Rossion B, Jacques C (2008) Does physical interstimulus variance account for early electrophysiological face sensitive responses in the human brain? Ten lessons on the N170. NeuroImage 39(4):1959–1979. S1053–8119(07)00936–6. https://doi.org/10.1016/j.neuroimage.2007.10.011CrossRefPubMedGoogle Scholar
  93. Rotshtein P, Henson RN, Treves A, Driver J, Dolan RJ (2005) Morphing Marilyn into Maggie dissociates physical and identity face representations in the brain. Nat Neurosci 8(1):107–113. https://doi.org/10.1038/nn1370CrossRefPubMedGoogle Scholar
  94. Schafer CB, Morgan BR, Ye AX, Taylor MJ, Doesburg SM (2014) Oscillations, networks, and their development: MEG connectivity changes with age. Hum Brain Mapp 35(10):5249–5261. https://doi.org/10.1002/hbm.22547CrossRefPubMedGoogle Scholar
  95. Scherf KS, Luna B, Avidan G, Behrmann M (2011) “What” precedes “which”: developmental neural tuning in face- and place-related cortex. Cereb Cortex 21(9):1963–1980. https://doi.org/10.1093/cercor/bhq269CrossRefPubMedPubMedCentralGoogle Scholar
  96. Segalowitz SJ, Santesso DL, Jetha MK (2010) Electrophysiological changes during adolescence: a review. Brain Cogn 72(1):86–100. https://doi.org/10.1016/j.bandc.2009.10.003CrossRefPubMedGoogle Scholar
  97. Singh KD (2012) Which “neural activity” do you mean? fMRI, MEG, oscillations and neurotransmitters. NeuroImage 62(2):1121–1130. https://doi.org/10.1016/j.neuroimage.2012.01.028CrossRefPubMedPubMedCentralGoogle Scholar
  98. Smith K, Politte D, Reiker G, Nolan TS, Hildebolt C, Mattson C, Larson-Prior LJ (2012) Automated measurement of pediatric cranial bone thickness and density from clinical computed tomography. Conf Proc IEEE Eng Med Biol Soc 2012:4462–4465. https://doi.org/10.1109/EMBC.2012.6346957CrossRefPubMedPubMedCentralGoogle Scholar
  99. Sporns, O (2011) Networks of the brain. The MIT Press, Cambridge, MassachusettsGoogle Scholar
  100. Srinivasan R (1999) Spatial structure of the human alpha rhythm: global correlation in adults and local correlation in children. Clin Neurophysiol 110(8):1351–1362CrossRefGoogle Scholar
  101. Stam CJ (2014) Modern network science of neurological disorders. Nat Rev Neurosci 15(10):683–695. https://doi.org/10.1038/nrn3801CrossRefPubMedGoogle Scholar
  102. Stam CJ, van Straaten ECW (2012) The organization of physiological brain networks. Clin Neurophysiol 123(6):1067–1087. https://doi.org/10.1016/j.clinph.2012.01.011CrossRefPubMedPubMedCentralGoogle Scholar
  103. Stam CJ, Tewarie P, Van Dellen E, van Straaten EC, Hillebrand A, Van Mieghem P (2014) The trees and the forest: Characterization of complex brain networks with minimum spanning trees. Int J Psychophysiol 92(3):129–138. https://doi.org/10.1016/j.ijpsycho.2014.04.001CrossRefPubMedGoogle Scholar
  104. Supekar K, Musen M, Menon V (2009) Development of large-scale functional brain networks in children. PLoS Biology 7(7):e1000157. https://doi.org/10.1371/journal.pbio.1000157CrossRefPubMedPubMedCentralGoogle Scholar
  105. Tang H, Brock J, Johnson BW (2016) Sound envelope processing in the developing human brain: a MEG study. Clin Neurophysiol 127(2):1206–1215. https://doi.org/10.1016/j.clinph.2015.07.038CrossRefPubMedPubMedCentralGoogle Scholar
  106. Taylor MJ, Pang EW (2014) MEG and Cognitive Developmental Studies. In: Supek S, Aine CJ (eds) Magnetoencephalography: from signals to dynamic cortical networks. Springer, New York, pp 557–577Google Scholar
  107. Taylor MJ, Batty M, Itier RJ (2004) The faces of development: a review of early face processing over childhood. J Cogn Neurosci 16(8):1426–1442. https://doi.org/10.1162/0898929042304732CrossRefPubMedGoogle Scholar
  108. Taylor MJ, Mills T, Zhang L, Pang EW (2010) Face processing in children: novel MEG findings. In: Supek S, Sušac A (eds) 17th international conference on biomagnetism advances in biomagnetism – biomag. Springer, Berlin, pp 314–317CrossRefGoogle Scholar
  109. Tesan G, Johnson BW, Reid M, Thornton R, Crain S (2010) Measurement of neuromagnetic brain function in pre-school children with custom sized MEG. J Vis Expt (36). https://doi.org/10.3791/1693
  110. Tewarie P, van Dellen E, Hillebrand A, Stam CJ (2015) The minimum spanning tree: an unbiased method for brain network analysis. NeuroImage 104:177–188. https://doi.org/10.1016/j.neuroimage.2014.10.015CrossRefPubMedGoogle Scholar
  111. Thatcher RW (1992) Cyclic cortical reorganization during early childhood. Brain Cogn 20(1):24–50CrossRefGoogle Scholar
  112. Thatcher RW, North DM, Biver CJ (2008) Development of cortical connections as measured by EEG coherence and phase delays. Hum Brain Mapp 29(12):1400–1415. https://doi.org/10.1002/hbm.20474CrossRefPubMedGoogle Scholar
  113. Thieba C, Frayne A, Walton M, Mah A, Benischek A, Dewey D, Lebel C (2018) Time efficient preparation methods for MRI brain scanning in awake young children and factors associated with success. BioRxiv. Preprint. https://doi.org/10.1101/259358
  114. Thorpe SG, Cannon EN, Fox NA (2016) Spectral and source structural development of mu and alpha rhythms from infancy through adulthood. Clin Neurophysiol 127(1):254–269. https://doi.org/10.1016/j.clinph.2015.03.004CrossRefPubMedGoogle Scholar
  115. Toth B, Urban G, Haden GP, Mark M, Torok M, Stam CJ, Winkler I (2017) Large-scale network organization of EEG functional connectivity in newborn infants. Hum Brain Mapp 38(8):4019–4033. https://doi.org/10.1002/hbm.23645CrossRefPubMedGoogle Scholar
  116. Uhlhaas PJ, Singer W (2011) The development of neural synchrony and large-scale cortical networks during adolescence: relevance for the pathophysiology of schizophrenia and neurodevelopmental hypothesis. Schiz Bull 37(3):514–523. https://doi.org/10.1093/schbul/sbr034CrossRefGoogle Scholar
  117. Uhlhaas PJ, Roux F, Singer W, Haenschel C, Sireteanu R, Rodriguez E (2009) The development of neural synchrony reflects late maturation and restructuring of functional networks in humans. Proc Nat Acad Sci USA 106(24):9866–9871. https://doi.org/10.1073/pnas.0900390106CrossRefPubMedGoogle Scholar
  118. Uhlhaas PJ, Roux F, Rodriguez E, Rotarska-Jagiela A, Singer W (2010) Neural synchrony and the development of cortical networks. Trend Cog Sci 14(2):72–80. https://doi.org/10.1016/j.tics.2009.12.002CrossRefGoogle Scholar
  119. Valdes-Hernandez PA, Ojeda-Gonzalez A, Martinez-Montes E, Lage-Castellanos A, Virues-Alba T, Valdes-Urrutia L, Valdes-Sosa PA (2010) White matter architecture rather than cortical surface area correlates with the EEG alpha rhythm. NeuroImage 49(3):2328–2339. https://doi.org/10.1016/j.neuroimage.2009.10.030CrossRefPubMedGoogle Scholar
  120. van Dellen E, Douw L, Hillebrand A, de Witt Hamer PC, Baayen JC, Heimans JJ, Stam CJ (2014) Epilepsy surgery outcome and functional network alterations in longitudinal MEG: a minimum spanning tree analysis. NeuroImage 86:354–363. https://doi.org/10.1016/j.neuroimage.2013.10.010CrossRefPubMedGoogle Scholar
  121. van Dellen E, Douw L, Hillebrand A, de Witt Hamer PC, Baayen JC, Heimans JJ, Reijneveld JC, Stam CJ (2018) Minimum spanning tree analysis of the human connectome. Hum Brain Mapp. https://doi.org/10.1002/hbm.24014CrossRefGoogle Scholar
  122. van den Heuvel MP, Kersbergen KJ, de Reus MA, Keunen K, Kahn RS, Groenendaal F, de Vries LS, Benders MJ (2015) The neonatal connectome during preterm brain development. Cereb Cortex 25(9):3000–3013. https://doi.org/10.1093/cercor/bhu095CrossRefPubMedGoogle Scholar
  123. van Wijk BC, Stam CJ, Daffertshofer A (2010) Comparing brain networks of different size and connectivity density using graph theory. PLoS One 5(10):e13701. https://doi.org/10.1371/journal.pone.0013701CrossRefPubMedPubMedCentralGoogle Scholar
  124. Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393(6684):440–442. https://doi.org/10.1038/30918CrossRefGoogle Scholar
  125. Webb SJ, Shell AR, Cuomo J, Jensen G, Deutsch CK (2012) Head circumference measurement and rrowth: Application to neurodevelopment. In: Preedy VR (ed) Handbook of growth and growth monitoring in health and disease. Springer, New York, pp 2981–2997CrossRefGoogle Scholar
  126. Wehner DT, Hamalainen MS, Mody M, Ahlfors SP (2008) Head movements of children in MEG: quantification, effects on source estimation, and compensation. NeuroImage 40(2):541–550. https://doi.org/10.1016/j.neuroimage.2007.12.026CrossRefPubMedPubMedCentralGoogle Scholar
  127. Witton C, Furlong PL, Seri S (2014) Technological challenges of pediatric MEG and potential solutions: the Aston Experience. In: Supek S, Aine CJ (eds) Magnetoencephalography: from signals to dynamic cortical networks. Springer, New York, pp 645–655Google Scholar
  128. Witton C, Talcott JB, Henning GB (2017) Psychophysical measurements in children: challenges, pitfalls, and considerations. PeerJ 5:e3231. https://doi.org/10.7717/peerj.3231CrossRefPubMedPubMedCentralGoogle Scholar
  129. Wu K, Taki Y, Sato K, Hashizume H, Sassa Y, Takeuchi H, Thyreau B, He Y, Evans AC, Li X, Kawashima R, Fukuda H (2013) Topological organization of functional brain networks in healthy children: differences in relation to age, sex, and intelligence. PLoS One 8(2):e55347. https://doi.org/10.1371/journal.pone.0055347CrossRefPubMedPubMedCentralGoogle Scholar
  130. Yap PT, Fan Y, Chen Y, Gilmore JH, Lin W, Shen D (2011) Development trends of white matter connectivity in the first years of life. PLoS One 6(9):e24678. https://doi.org/10.1371/journal.pone.0024678CrossRefPubMedPubMedCentralGoogle Scholar
  131. Yu M, Gouw AA, Hillebrand A, Tijms BM, Stam CJ, van Straaten EC, Pijnenburg YA (2016) Different functional connectivity and network topology in behavioral variant of frontotemporal dementia and Alzheimer’s disease: an EEG study. Neurob Aging 42:150–162. https://doi.org/10.1016/j.neurobiolaging.2016.03.018CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Cognitive ScienceMacquarie UniversitySydneyAustralia

Section editors and affiliations

  • Julia M. Stephen
    • 1
  1. 1.The Mind Research NetworkAlbuquerqueUSA

Personalised recommendations