Abstract
Background
The white matter (WM) connectome is important for cognitive development and intelligence
and is altered in neuropsychiatric illnesses. Little is known about how the WM connectome
develops or its relationship to IQ in early childhood.
Methods
The development of node centrality in the WM connectome was studied in a longitudinal
cohort of 226 (123 female) children from the University of North Carolina Early Brain
Development Study. Structural and diffusion-weighted images were acquired after birth
and at 1, 2, 4, and 6 years, and IQ was assessed at 6 years. Eigenvector centrality,
betweenness centrality, and the global graph metrics of global efficiency, small worldness,
and modularity were determined at each age.
Results
The greatest developmental change in eigenvector centrality and betweenness centrality
occurred during the first year of life, with relative stability between ages 1 and
6 years. Most of the high-centrality hubs at age 6 were also high-centrality hubs
at 1 year, and many were already high-centrality hubs at birth. There were generally
small but significant changes in global efficiency and modularity from birth to 6
years, while small worldness increased between 2 and 4 years. Individual node centrality
was not significantly correlated with IQ at 6 years.
Conclusions
Node centrality in the WM connectome is established very early in childhood and is
relatively stable from age 1 to 6 years. Many high-centrality hubs are established
before birth, and most are present by age 1.
Keywords
To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Biological Psychiatry: Cognitive Neuroscience and NeuroimagingAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- High-cost high-capacity backbone for global brain communication.Proc Natl Acad Sci U S A. 2012; 109: 11372-11377
- Brain anatomical network and intelligence.PLoS Comput Biol. 2009; 5e1000395
- Children’s academic attainment is linked to the global organization of the white matter connectome.Dev Sci. 2018; 21e12662
- Whole-brain white matter organization, intelligence, and educational attainment.Trends Neurosci Educ. 2019; 15: 38-47
- White matter microarchitecture and structural network integrity correlate with children intelligence quotient.Sci Rep. 2020; 1020722
- The hubs of the human connectome are generally implicated in the anatomy of brain disorders.Brain. 2014; 137: 2382-2395
- White matter disruptions in schizophrenia are spatially widespread and topologically converge on brain network hubs.Schizophr Bull. 2017; 43: 425-435
- A cross-disorder connectome landscape of brain dysconnecitivity.Nat Rev Neurosci. 2019; 20: 435-446
- Shared vulnerability for connectome alterations across psychiatric and neurological brain disorders.Nat Hum Behav. 2019; 3: 988-998
- White matter maturation reshapes structural connectivity in the late developing human brain.Proc Natl Acad Sci U S A. 2010; 107: 19067-19072
- Development trends of white matter connectivity in the first years of life.PLoS One. 2011; 6e24678
- Development of human brain structural networks through infancy and childhood.Cereb Cortex. 2015; 25: 1389-1404
- Rich-club organization of the newborn human brain.Proc Natl Acad Sci U S A. 2014; 111: 7456-7461
- The neonatal connectome during preterm brain development.Cereb Cortex. 2015; 25: 3000-3013
- Early development of structural networks and the impact of prematurity on brain connectivity.NeuroImage. 2017; 149: 379-392
- Toward developmental connectomics of the human brain.Front Neuroanat. 2016; 10: 25
- The development of brain network hubs.Dev Cogn Neurosci. 2019; 36100607
- Network hubs in the human brain.Trends Cogn Sci. 2013; 17: 683-696
- Using diffusion tractography to predict cortical connection strength and distance: A quantitative comparison with tracers in the monkey.J Neurosci. 2016; 36: 6758-6770
- A macaque connectome for large-scale network simulations in TheVirtualBrain.Sci Data. 2019; 6: 123
- Exploring the limits of network topology estimation using diffusion-based tractography and tracer studies in the macaque cortex.NeuroImage. 2019; 191: 81-92
- Circuits, networks, and neuropsychiatric disease: Transitioning from anatomy to imaging.Biol Psychiatry. 2020; 87: 318-327
- Network-level structure-function relationships in human neocortex.Cereb Cortex. 2016; 26: 3285-3296
- Complex network measures of brain connectivity: Uses and interpretations.NeuroImage. 2010; 52: 1059-1069
- Imaging structural and functional brain development in early childhood.Nat Rev Neurosci. 2018; 19: 123-137
- Subdural hemorrhage in asymptomatic neonates: Neurodevelopmental outcomes and MRI findings at 2 years.Radiology. 2021; 298: 173-179
- Structured Clinical Interview for DSM-IV (SCID): Encycl Behav Med.Springer, New York2013 (New York, 1919–1920)
- Test review: Roid GH (2003).Stanford-Binet Intelligence Scales, Fifth Edition (SB:V). Itasca, IL: Riverside Publishing. Can J Sch Psychol. 2004; 19: 235-244
- Cortical structure and cognition in infants and toddlers.Cereb Cortex. 2020; 30: 786-800
- Individual variation of human cortical structure is established in the first year of life.Biol Psychiatry Cogn Neurosci Neuroimaging. 2020; 5: 971-980
- Multi-atlas segmentation of subcortical brain structures via the AutoSeg software pipeline.Front Neuroinform. 2014; 8: 7
- Development of cortical surface area and gyrification in attention-deficit/hyperactivity disorder.Biol Psychiatry. 2012; 72: 191-197
- Neurodevelopmental trajectories of the human cerebral cortex.J Neurosci. 2008; 28: 3586-3594
- Automatic segmentation of MR images of the developing newborn brain.Med Image Anal. 2005; 9: 457-466
- Genetic influences on neonatal cortical thickness and surface area.Hum Brain Mapp. 2018; 39: 4998-5013
- Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.Neuroimage. 2002; 15: 273-289
- DTIPrep: Quality control of diffusion-weighted images.Front Neuroinform. 2014; 8: 4
- A reproducible evaluation of ANTs similarity metric performance in brain image registration.Neuroimage. 2011; 54: 2033-2044
- CIVILITY: Cloud based interactive visualization of tractography brain connectome.Proc SPIE Int Soc Opt Eng. 2017; 10137
- Conn: A functional connectivity toolbox for correlated and anticorrelated brain networks.Brain Connect. 2012; 2: 125-141
- Harmonization of cortical thickness measurements across scanners and sites.NeuroImage. 2018; 167: 104-120
- White matter development from birth to 6 years of age: A longitudinal study.Cereb Cortex. 2020; 30: 6152-6168
- Development of structure-function coupling in human brain networks during youth.Proc Natl Acad Sci U S A. 2020; 117: 771-778
- Development of human brain cortical network architecture during infancy.Brain Struct Funct. 2015; 220: 1173-1186
- Developmental connectomics from infancy through early childhood.Trends Neurosci. 2017; 40: 494-506
- Developmental heatmaps of brain functional connectivity from newborns to 6-year-olds.Dev Cogn Neurosci. 2021; 50100976
- Rich-club organization of the human connectome.J Neurosci. 2011; 31: 15775-15786
- Graph theoretical analysis of developmental patterns of the white matter network.Front Hum Neurosci. 2013; 7: 716
- Conservation of brain connectivity and wiring across the mammalian class.Nat Neurosci. 2020; 23: 805-808
- Mechanisms of connectome development.Trends Cogn Sci. 2017; 21: 703-717
- Spatiotemporal ontogeny of brain wiring.Sci Adv. 2019; 5eaav9694
- Genetic influences on hub connectivity of the human connectome.Nat Commun. 2021; 12: 4237
- Sex differences in the structural connectome of the human brain.Proc Natl Acad Sci U S A. 2014; 111: 823-828
- Hemisphere and gender differences in the rich-club organization of structural networks.Cereb Cortex. 2019; 29: 4889-4901
- Sex differences in the developing brain: Insights from multimodal neuroimaging.Neuropsychopharmacology. 2019; 44: 71-85
- Diffusion MRI of white matter microstructure development in childhood and adolescence: Methods, challenges and progress.Dev Cogn Neurosci. 2018; 33: 161-175
- BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment.Neuroimage. 2017; 146: 1038-1049
- White matter connectomes at birth accurately predict cognitive abilities at age 2.NeuroImage. 2019; 192: 145-155
- Personalized connectome fingerprints: Their importance in cognition from childhood to adult years.Neuroimage. 2020; 221117122
- Early prediction of cognitive deficit in very preterm infants using brain structural connectome with transfer learning enhanced deep convolutional neural networks.Front Neurosci. 2020; 14: 858
- The white matter connectome as an early imaging biomarker.Biol Psychiatry. 2021; 89
- Children’s intellectual ability is associated with structural network integrity.NeuroImage. 2016; 124: 550-556
- BrainNet Viewer: A network visualization tool for human brain connectomics.PLoS One. 2013; 8e68910
Article info
Publication history
Published online: September 23, 2022
Accepted:
September 9,
2022
Received in revised form:
September 7,
2022
Received:
February 8,
2022
Publication stage
In Press Journal Pre-ProofIdentification
Copyright
© 2022 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
