Literature DB >> 33280008

Hierarchical Complexity of the Macro-Scale Neonatal Brain.

Manuel Blesa1, Paola Galdi1, Simon R Cox2, Gemma Sullivan1, David Q Stoye1, Gillian J Lamb1, Alan J Quigley3, Michael J Thrippleton4,5, Javier Escudero6, Mark E Bastin4, Keith M Smith7,8, James P Boardman1,4.   

Abstract

The human adult structural connectome has a rich nodal hierarchy, with highly diverse connectivity patterns aligned to the diverse range of functional specializations in the brain. The emergence of this hierarchical complexity in human development is unknown. Here, we substantiate the hierarchical tiers and hierarchical complexity of brain networks in the newborn period, assess correspondences with hierarchical complexity in adulthood, and investigate the effect of preterm birth, a leading cause of atypical brain development and later neurocognitive impairment, on hierarchical complexity. We report that neonatal and adult structural connectomes are both composed of distinct hierarchical tiers and that hierarchical complexity is greater in term born neonates than in preterms. This is due to diversity of connectivity patterns of regions within the intermediate tiers, which consist of regions that underlie sensorimotor processing and its integration with cognitive information. For neonates and adults, the highest tier (hub regions) is ordered, rather than complex, with more homogeneous connectivity patterns in structural hubs. This suggests that the brain develops first a more rigid structure in hub regions allowing for the development of greater and more diverse functional specialization in lower level regions, while connectivity underpinning this diversity is dysmature in infants born preterm.
© The Author(s) 2020. Published by Oxford University Press.

Entities:  

Keywords:  dMRI; developing brain; hierarchical complexity; network analysis; newborn; structural connectome

Mesh:

Year:  2021        PMID: 33280008      PMCID: PMC7945030          DOI: 10.1093/cercor/bhaa345

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


  71 in total

1.  Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging.

Authors:  T E J Behrens; H Johansen-Berg; M W Woolrich; S M Smith; C A M Wheeler-Kingshott; P A Boulby; G J Barker; E L Sillery; K Sheehan; O Ciccarelli; A J Thompson; J M Brady; P M Matthews
Journal:  Nat Neurosci       Date:  2003-07       Impact factor: 24.884

2.  A Bayesian model of shape and appearance for subcortical brain segmentation.

Authors:  Brian Patenaude; Stephen M Smith; David N Kennedy; Mark Jenkinson
Journal:  Neuroimage       Date:  2011-02-23       Impact factor: 6.556

3.  Multiscale Structure-Function Gradients in the Neonatal Connectome.

Authors:  Sara Larivière; Reinder Vos de Wael; Seok-Jun Hong; Casey Paquola; Shahin Tavakol; Alexander J Lowe; Dewi V Schrader; Boris C Bernhardt
Journal:  Cereb Cortex       Date:  2020-01-10       Impact factor: 5.357

4.  Connectomes from streamlines tractography: Assigning streamlines to brain parcellations is not trivial but highly consequential.

Authors:  Chun-Hung Yeh; Robert E Smith; Thijs Dhollander; Fernando Calamante; Alan Connelly
Journal:  Neuroimage       Date:  2019-05-11       Impact factor: 6.556

5.  Fiber tractography using machine learning.

Authors:  Peter F Neher; Marc-Alexandre Côté; Jean-Christophe Houde; Maxime Descoteaux; Klaus H Maier-Hein
Journal:  Neuroimage       Date:  2017-07-15       Impact factor: 6.556

6.  The emergence of functional architecture during early brain development.

Authors:  Kristin Keunen; Serena J Counsell; Manon J N L Benders
Journal:  Neuroimage       Date:  2017-01-20       Impact factor: 6.556

7.  Multi-Atlas Segmentation with Joint Label Fusion.

Authors:  Hongzhi Wang; Jung W Suh; Sandhitsu R Das; John B Pluta; Caryne Craige; Paul A Yushkevich
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2012-06-26       Impact factor: 6.226

8.  Automatic whole brain MRI segmentation of the developing neonatal brain.

Authors:  Antonios Makropoulos; Ioannis S Gousias; Christian Ledig; Paul Aljabar; Ahmed Serag; Joseph V Hajnal; A David Edwards; Serena J Counsell; Daniel Rueckert
Journal:  IEEE Trans Med Imaging       Date:  2014-05-06       Impact factor: 10.048

9.  Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction.

Authors:  Matteo Bastiani; Michiel Cottaar; Sean P Fitzgibbon; Sana Suri; Fidel Alfaro-Almagro; Stamatios N Sotiropoulos; Saad Jbabdi; Jesper L R Andersson
Journal:  Neuroimage       Date:  2018-09-26       Impact factor: 6.556

Review 10.  Invited Review: Factors associated with atypical brain development in preterm infants: insights from magnetic resonance imaging.

Authors:  J P Boardman; S J Counsell
Journal:  Neuropathol Appl Neurobiol       Date:  2019-12-12       Impact factor: 8.090

View more
  3 in total

1.  Brain network reorganisation and spatial lesion distribution in systemic lupus erythematosus.

Authors:  Maria Del C Valdés Hernández; Keith Smith; Mark E Bastin; E Nicole Amft; Stuart H Ralston; Joanna M Wardlaw; Stewart J Wiseman
Journal:  Lupus       Date:  2020-12-13       Impact factor: 2.911

2.  Structural connectivity of the sensorimotor network within the non-lesioned hemisphere of children with perinatal stroke.

Authors:  Brandon T Craig; Eli Kinney-Lang; Alicia J Hilderley; Helen L Carlson; Adam Kirton
Journal:  Sci Rep       Date:  2022-03-09       Impact factor: 4.379

3.  Typical and disrupted brain circuitry for conscious awareness in full-term and preterm infants.

Authors:  Huiqing Hu; Rhodri Cusack; Lorina Naci
Journal:  Brain Commun       Date:  2022-03-24
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.