Cited by 71Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity StudiesFetal and Pediatric Neurological Disorders

Human fetal brain connectome: structural network development from middle fetal stage to birth

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Song, Limei, Mishra, Virendra, Ouyang, Minhui, Peng, Qinmu, Slinger, Michelle, Liu, Shuwei, Huang, Hao·2017·Frontiers in Neuroscience

Abstract

Complicated molecular and cellular processes take place in a spatiotemporally heterogeneous and precisely regulated pattern in the human fetal brain, yielding not only dramatic morphological and microstructural changes, but also macroscale connectomic transitions. As the underlying substrate of the fetal brain structural network, both dynamic neuronal migration pathways and rapid developing fetal white matter (WM) fibers could fundamentally reshape early fetal brain connectome. Quantifying structural connectome development can not only shed light on the brain reconfiguration in this critical yet rarely studied developmental period, but also reveal alterations of the connectome under neuropathological conditions. However, transition of the structural connectome from the mid-fetal stage to birth is not yet known. The contribution of different types of neural fibers to the structural network in the mid-fetal brain is not known, either. In this study, diffusion tensor magnetic resonance imaging (DT-MRI or DTI) of 10 fetal brain specimens at the age of 20 postmenstrual weeks (PMW), 12 in vivo brains at 35 PMW and 12 in vivo brains at term (40 PMW) were acquired. The structural connectome of each brain was established with evenly parcellated cortical regions as network nodes and traced fiber pathways based on DTI tractography as network edges. Two groups of fibers were categorized based on the fiber terminal locations in the cerebral wall in the 20PMW fetal brains. We found that fetal brain networks become stronger and more efficient during 20-40 PMW. Furthermore, network strength and global efficiency increase more rapidly during 20-35PMW than during 35-40PMW. Visualization of the whole brain fiber distribution by the lengths suggested that the network reconfiguration in this developmental period could be associated with a significant increase of major long association WM fibers. In addition, non-WM neural fibers could be a major contributor to the structural network configuration at 20PMW and small-world network organization could exist as early as 20PMW. These findings offer a preliminary record of the fetal brain structural connectome maturation from the middle fetal stage to birth and reveal the critical role of non-WM neural fibers in structural network configuration in the middle fetal stage.

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  • Fetal brain structural connectivity shows adult-like topological organization, including significant small-world, modular, and rich-club organization, during the middle to final trimester of gestation.

    “Many studies have discovered largely adult-like topological structures including significant small-world, modular, and rich-club organization during the middle to final trimester of gestation”

    From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Song et al., 2017

    The Results report small-world organization in fetal structural networks at 20, 35, and 40 postmenstrual weeks (Figures 6–7; page not provided). The passages do not establish modular or rich-club organization, or characterize the topology as broadly adult-like. (LLM, conf=0.88)

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  1. Basser P. J. Mattiello J. LeBihan D. (1994). Estimation of the effective self-diffusion tensor from the NMR spin echo. J. Magn. Reson. B103, 247– 254. 10.1006/jmrb.1994.1037 8019776 · DOI
  2. Bassett D. S. Bullmore E. Verchinski B. A. Mattay V. S. Weinberger D. R. Meyer-Lindenberg A. (2008). Hierarchical organization of human cortical networks in health and schizophrenia. J. Neurosci. 28, 9239– 9248. 10.1523/JNEUROSCI.1929-08.2008 18784304 PMC2878961 · DOI
  3. Bourgeois J. P. Jastreboff P. J. Rakic P. (1989). Synaptogenesis in visual cortex of normal and preterm monkeys: evidence for intrinsic regulation of synaptic overproduction. Proc. Natl. Acad. Sci. U.S.A. 86, 4297– 4301. 10.1073/pnas.86.11.4297 2726773 PMC287439 · DOI
  4. Brown C. J. Miller S. P. Booth B. G. Andrews S. Chau V. Poskitt K. J.. (2014). Structural network analysis of brain development in young preterm neonates. Neuroimage 101, 667– 680. 10.1016/j.neuroimage.2014.07.030 25076107 · DOI · Paper page
  5. Cao M. He Y. Dai Z. Liao X. Jeon T. Ouyang M.. (2017). Early development of functional network segregation revealed by connectomic analysis of the preterm human brain. Cereb. Cortex 27, 1949– 1963. 10.1093/cercor/bhw038. 26941380 PMC6059235 · DOI
  6. Catani M. Thiebaut de Schotten M. (2008). A diffusion tensor imaging tractography for virtual in vivo dissections. Cortex 44, 1105– 1132. 10.1016/j.cortex.2008.05.004 18619589 · DOI · Paper page
  7. Doria V. Beckmann C. F. Arichi T. Merchant N. Groppo M. Turkheimer F. E.. (2010). Emergence of resting state networks in the preterm human brain. Proc. Natl. Acad. Sci. U.S.A. 107, 20015– 20020. 10.1073/pnas.1007921107 21041625 PMC2993415 · DOI · Paper page
  8. Engle W. A. American academy of pediatrics committee on fetus and newborn. (2004). Age terminology during the perinatal period. Pediatrics 114, 1362– 1364. 10.1542/peds.2004-1915 15520122 · DOI
  9. Fransson P. Skiold B. Horsch S. Nordell A. Blennow M. Lagercrantz H. (2007). Resting-state networks in the infant brain. Proc. Natl. Acad. Sci. U.S.A. 104, 15531– 15536. 10.1073/pnas.0704380104 17878310 PMC2000516 · DOI · Paper page
  10. Greicius M. D. Supekar K. Menon V. Dougherty R. F. (2009). Resting-state functional connectivity reflects structural connectivity in the default mode network. Cereb. Cortex 19, 72– 78. 10.1093/cercor/bhn059 18403396 PMC2605172 · DOI · Paper page
  11. Hagmann P. Cammoun L. Gigandet X. Meuli R. Honey C. J. Wedeen V. J.. (2008). Mapping the structural core of human cerebral cortex. PLoS Biol. 6: e159. 10.1371/journal.pbio.0060159 18597554 PMC2443193 · DOI · Paper page
  12. Hagmann P. Sporns O. Madan N. Cammoun L. Pienaar R. Wedeen V. J.. (2010). White matter maturation reshapes structural connectivity in the late developing human brain. Proc. Natl. Acad. Sci. U.S.A. 107, 19067– 19072. 10.1073/pnas.1009073107 20956328 PMC2973853 · DOI · Paper page
  13. Honey C. J. Sporns O. Cammoun L. Gigandet X. Thiran J. P. Meuli R.. (2009). Predicting human resting-state functional connectivity from structural connectivity. Proc. Natl. Acad. Sci. U.S.A. 106, 2035– 2040. 10.1073/pnas.0811168106 19188601 PMC2634800 · DOI · Paper page
  14. Huang H. (2010). Structure of the fetal brain: what we are learning from DTI. Neuroscientist 16, 634– 649. 10.1177/1073858409356711 20360600 · DOI
  15. Huang H. Jeon T. Sedmak G. Pletikos M. Vasung L. Xu X.. (2013). Coupling diffusion imaging with histological and gene expression analysis to examine the dynamics of cortical areas across the fetal period of human brain development. Cereb. Cortex 23, 2620– 2631. 10.1093/cercor/bhs241 22933464 PMC3792738 · DOI
  16. Huang H. Shu N. Mishra V. Jeon T. Chalak L. Wang Z. J.. (2015). Development of human brain structural networks through infancy and childhood. Cereb. Cortex 25, 1389– 1404. 10.1093/cercor/bht335 24335033 PMC4397575 · DOI · Paper page
  17. Huang H. Vasung L. (2014). Gaining insight of fetal brain development with diffusion MRI and histology. Int. J. Dev. Neurosci. 21, 00102– 00100. 10.1016/j.ijdevneu.2013.06.005 PMC3825830 23796901 · DOI
  18. Huang H. Xue R. Zhang J. Ren T. Richards L. J. Yarowsky P.. (2009). Anatomical characterization of human fetal brain development with diffusion tensor magnetic resonance imaging. J. Neurosci. 29, 4263– 4273. 10.1523/JNEUROSCI.2769-08.2009 19339620 PMC2721010 · DOI · Paper page
  19. Huang H. Zhang J. Wakana S. Zhang W. Ren T. Richards L. J.. (2006). White and gray matter development in human fetal, newborn and pediatric brains. Neuroimage 33, 27– 38. 10.1016/j.neuroimage.2006.06.009 16905335 · DOI
  20. Innocenti G. M. Price D. J. (2005). Exuberance in the development of cortical networks. Nat. Rev. Neurosci. 6, 955– 965. 10.1038/nrn1790 16288299 · DOI · Paper page
  21. Jakab A. Schwartz E. Kasprian G. Gruber G. M. Prayer D. Schöpf V.. (2014). Fetal functional imaging portrays heterogeneous development of emerging human brain networks. Front. Hum. Neurosci. 8: 852. 10.3389/fnhum.2014.00852 25374531 PMC4205819 · DOI · Paper page
  22. Jeon T. Mishra V. Ouyang M. Chen M. Huang H. (2015). Synchronous changes of cortical thickness and corresponding white matter microstructure during brain development accessed by diffusion MRI tractography from parcellated cortex. Front. Neuroanat. 9: 158. 10.3389/fnana.2015.00158 26696839 PMC4667005 · DOI
  23. Jiang H. van Zijl P. C. M. Kim J. Pearlson G. D. Mori S. (2006). DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking. Comput. Methods Prog. Biomed. 81, 106– 116. 10.1016/j.cmpb.2005.08.004 16413083 · DOI
  24. Johnson M. B. Kawasawa Y. I. Mason C. E. Krsnik Z. Coppola G. Bogdanovic D.. (2009). Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 62, 494– 509. 10.1016/j.neuron.2009.03.027 19477152 PMC2739738 · DOI · Paper page
  25. Jones D. K. Horsfield M. A. Simmons A. (1999). Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn. Reson. Med. 42, 515– 525. 10.1002/(SICI)1522-2594(199909)42:3<515::AID-MRM14>3.0.CO;2-Q 10467296 · DOI
  26. Kasprian G. Brugger P. C. Weber M. Krssak M. Krampl E. Herold C.. (2008). In utero tractography of fetal white matter development. Neuroimage 43, 213– 224. 10.1016/j.neuroimage.2008.07.026 18694838 · DOI
  27. Kostović I. (1991). Structural and histochemical reorganization of the human prefrontal cortex during perinatal and postnatal life. Prog. Brain Res. 85, 223– 239. 10.1016/S0079-6123(08)62682-5 2094895 · DOI · Paper page
  28. Kostović I. Jovanov-Milošević N. (2006). The development of cerebral connections during the first 20–45 weeks' gestation. Semin. Fetal Neonatal Med. 11, 415– 422. 10.1016/j.siny.2006.07.001 16962836 · DOI
  29. Kostović I. Judas M. Rados M. Hrabac P. (2002). Laminar organization of the human fetal cerebrum revealed by histochemical markers and magnetic resonance imaging. Cereb. Cortex 12, 536– 544. 10.1093/cercor/12.5.536 11950771 · DOI
  30. Kostović I. Rakic P. (1984). Development of prestriate visual projections in the monkey and human fetal cerebrum revealed by transient cholinesterase staining. J. Neurosci. 4, 25– 42. 6693940 PMC6564757
  31. Kostović I. Rakic P. (1990). Developmental history of the transient subplate zone in the visual and somatosensory cortex of the macaque monkey and human brain. J. Comp. Neurol. 297, 441– 470. 10.1002/cne.902970309 2398142 · DOI
  32. Latora V. Marchiori M. (2001). Efficient behavior of small-world networks. Phys. Rev. Lett. 87: 198701. 10.1103/PhysRevLett.87.198701 11690461 · DOI · Paper page
  33. Leopardi P. (2006). A partition of the unit sphere into regions of equal area and small diameter. Electron. Trans. Numer. Anal. 25, 309– 327.
  34. Lui J. H. Hansen D. V. Kriegstein A. R. (2011). Development and evolution of the human neocortex. Cell 146, 18– 36. 10.1016/j.cell.2011.06.030 21729779 PMC3610574 · DOI · Paper page
  35. Mishra V. Cheng H. Gong G. He Y. Dong Q. Huang H. (2013). Differences of inter-tract correlations between neonates and children around puberty: a study based on microstructural measurements with DTI. Front. Hum. Neurosci. 7: 721. 10.3389/fnhum.2013.00721 24194711 PMC3810597 · DOI
  36. Mitter C. Prayer D. Brugger P. C. Weber M. Kasprian G. (2015b). In vivo tractography of fetal association fibers. PLoS ONE 10: e0119536. 10.1371/journal.pone.0119536 25742520 PMC4350986 · DOI
  37. Mori S. Crain B. J. Chacko V. P. van Zijl P. C. (1999). Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann. Neurol. 45, 265– 269. 10.1002/1531-8249(199902)45:2<265::AID-ANA21>3.0.CO;2-3 9989633 · DOI
  38. Ouyang A. Jeon T. Sunkin S. M. Pletikos M. Sedmak G. Sestan N.. (2015). Spatial mapping of structural and connectional imaging data for the developing human brain with diffusion tensor imaging. Methods 73, 27– 37. 10.1016/j.ymeth.2014.10.025 25448302 PMC4329045 · DOI
  39. Pandit A. S. Robinson E. Aljabar P. Ball G. Gousias I. S. Wang Z.. (2014). Whole-brian mapping of structural connectivity in infants reveals altered connection strength associated with growth and preterm birth. Cereb. Cortex 24, 2324– 2333. 10.1093/cercor/bht086 23547135 · DOI
  40. Pierpaoli C. Basser P. J. (1996). Toward a quantitative assessment of diffusion anisotropy. Magn. Reson. Med. 36, 893– 906. 10.1002/mrm.1910360612 8946355 · DOI
  41. Power J. D. Fair D. A. Schlaggar B. L. Petersen S. E. (2010). The development of human functional brain networks. Neuron 67, 735– 748. 10.1016/j.neuron.2010.08.017 20826306 PMC2941973 · DOI · Paper page
  42. Prettejohn B. J. Berryman M. J. McDonnell M. D. (2011). Methods for generating complex networks with selected structural properties for simulations: a review and tutorial for neuroscientists. Front. Comput. Neurosci. 5: 11. 10.3389/fncom.2011.00011 21441986 PMC3059456 · DOI
  43. Rakic P. (1972). Mode of cell migration to the superficial layers of fetal monkey neocortex. J. Comp. Neurol. 145, 61– 83. 10.1002/cne.901450105 4624784 · DOI · Paper page
  44. Rakic P. (1995). A small step for the cell—a giant leap for mankind: a hypothesis of neocortical expansion during evolution. Trends Neurosci. 18, 383– 388. 10.1016/0166-2236(95)93934-P 7482803 · DOI · Paper page
  45. Rubinov M. Sporns O. (2010). Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52, 1059– 1069. 10.1016/j.neuroimage.2009.10.003 19819337 · DOI · Paper page
  46. Sidman R. L. Rakic P. (1973). Neuronal migration, with specific reference to developing human brain: a review. Brain Res. 62, 1– 35. 10.1016/0006-8993(73)90617-3 4203033 · DOI
  47. Smyser C. D. Inder T. E. Shimony J. S. Hill J. E. Degnan A. J. Snyder A. Z.. (2010). Longitudinal analysis of neural network development in preterm infants. Cereb. Cortex 20, 2852– 2862. 10.1093/cercor/bhq035 20237243 PMC2978240 · DOI · Paper page
  48. Sporns O. Tononi G. Kötter R. (2005). The human connectome: a structural description of the human brain. PLoS Comput. Biol. 1: e42. 10.1371/journal.pcbi.0010042 16201007 PMC1239902 · DOI · Paper page
  49. Sun S. W. Neil J. J. Liang H. F. He Y. Y. Schmidt R. E. Hsu C. Y.. (2005). Formalin fixation alters water diffusion coefficient magnitude but not anisotropy in infracted brain. Magn. Reson. Med. 53, 1447– 1451. 10.1002/mrm.20488 15906292 · DOI · Paper page
  50. Sun S. W. Neil J. J. Song S. K. (2003). Relative indicies of water diffusion anisotropy are equivalent to live and formalin-fixed mouse brains. Magn. Reson. Med. 50, 743– 748. 10.1002/mrm.10605 14523960 · DOI · Paper page
  51. Supekar K. Musen M. Menon V. (2009). Development of large-scale functional brain networks in children. PLoS Biol. 7: e1000157. 10.1371/journal.pbio.1000157 19621066 PMC2705656 · DOI · Paper page
  52. Takahashi E. Folkerth R. D. Galaburda A. M. Grant P. E. (2012). Emerging cerebral connectivity in the human fetal brain: an MR tractography study. Cereb. Cortex 22, 455– 464. 10.1093/cercor/bhr126 21670100 PMC3256410 · DOI
  53. Thomason M. E. Dassanayake M. T. Shen S. Katkuri Y. Alexis M. Anderson A. L.. (2013). Cross-hemispheric functional connectivity in the human fetal brain. Sci. Transl. Med. 5: 173ra24. 10.1126/scitranslmed.3004978 23427244 PMC3618956 · DOI · Paper page
  54. Thomason M. E. Grove L. E. Lozon T. A. Vila A. M. Ye Y. Nye M. J.. (2015). Age-related increases in long-range connectivity in fetal functional neural connectivity networks in utero. Dev. Cogn. Neurosci. 11, 96– 104. 10.1016/j.dcn.2014.09.001 25284273 PMC4532276 · DOI
  55. Tymofiyeva O. Hess C. P. Ziv E. Tian N. Bonifacio S. L. McQuillen P. S.. (2012). Towards the “baby connectome”: mapping the structural connectivity of the newborn brain. PLoS ONE 7: e31029. 10.1371/journal.pone.0031029 22347423 PMC3274551 · DOI
  56. van den Heuvel M. I. Thomason M. E. (2016). Functional connectivity of the human brain in utero. Trends Cogn. Sci. 20, 931– 939. 10.1016/j.tics.2016.10.001 27825537 PMC5339022 · DOI
  57. Vasung L. Huang H. Jovanov-Milošević N. Pletikos M. Mori S. Kostović I. (2010). Development of axonal pathways in the human fetal fronto-limbic brain: histochemical characterization and diffusion tensor imaging. J. Anat. 217, 400– 417. 10.1111/j.1469-7580.2010.01260.x 20609031 PMC2992416 · DOI · Paper page
  58. Wakana S. Jiang H. Nagae-Poetscher L. M. Van Zijl P. C. Mori S. (2004). Fiber tract–based atlas of human white matter anatomy. Radiology 230, 77– 87. 10.1148/radiol.2301021640 14645885 · DOI
  59. Wang J. Wang X. Xia M. Liao X. Evans A. He Y. (2015). GRETNA: a graph theoretical network analysis toolbox for imaging connectomics. Front. Hum. Neurosci. 9: 386 10.3389/fnhum.2015.00386 26175682 PMC4485071 · DOI
  60. Wang R. Benner T. Sorensen A. G. Wedeen V. J. (2007). Diffusion toolkit: a software package for diffusion imaging data processing and tractography. Proc. Intl. Soc. Mag. Reson. Med. 15, 3720.
  61. Watts D. J. Strogatz S. H. (1998). Collective dynamics of “small-world” networks. Nature 393, 440– 442. 10.1038/30918 9623998 · DOI · Paper page
  62. Woods R. P. Grafton S. T. Holmes C. J. Cherry S. R. Mazziotta J. C. (1998). Automated image registration: I. General methods and intrasubject, intramodality validation. J. Comput. Assist. Tomogr. 22, 139– 152. 10.1097/00004728-199801000-00027 9448779 · DOI
  63. Woodward L. J. Anderson P. J. Austin N. C. Howard K. Inder T. E. (2006). Neonatal MRI to predict neurodevelopmental outcomes in preterm infants. New Engl. J. Med. 355, 685– 694. 10.1056/NEJMoa053792 16914704 · DOI
  64. Xu G. Takahashi E. Folkerth R. D. Haynes R. L. Volpe J. J. Grant P. E.. (2014). Radial coherence of diffusion tractography in the cerebral white matter of the human fetus: neuroanatomic insights. Cereb. Cortex 24, 579– 592. 10.1093/cercor/bhs330 23131806 PMC3920761 · DOI
  65. Yu Q. Ouyang A. Chalak L. Jeon T. Chia J. Mishra V.. (2016). Structural development of human fetal and preterm brain cortical plate based on population-averaged templates. Cereb. Cortex 26, 4381– 4391. 10.1093/cercor/bhv201 26405055 PMC5066822 · DOI

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Sorted by citations

Authors
Song, L., Mishra, V., Ouyang, M., Peng, Q., Slinger, M., Liu, S., & Huang, H.
Affiliations
  • Children's Hospital of Philadelphia (US)
  • Cleveland Clinic (US)
  • Shandong University (CN)
Corresponding author
  • Liu, Shuwei
  • Huang, Hao
Venue
Frontiers in Neuroscience
Published
2017-10-13
Volume
11
Pages
561-561
ISSN
1662-453X (ISSN-L)
OpenAlex
W2762636258
Cited by
71
References
13
Citations by year
2026: 5 · 2025: 7 · 2024: 10 · 2023: 8 · 2022: 6 · 2021: 9 · 2020: 9 · 2019: 7 · 2018: 10
FWCI
5.46
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Frontiers in Neuroscience (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Office of Extramural Research, National Institutes of Health (MH092535, MH092535-S1)
  • National Natural Science Foundation of China (31571237)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Fetal and Pediatric Neurological Disorders
Keywords
fetal brain, structural connectome, brain network development, network efficiency, network strength, small-world networks, cortical parcellation, tractography, neuronal migration

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