Literature DB >> 32537627

Development of Microstructural and Morphological Cortical Profiles in the Neonatal Brain.

Daphna Fenchel1,2,3, Ralica Dimitrova2,3,4, Jakob Seidlitz5,6, Emma C Robinson7, Dafnis Batalle2,3,4, Jana Hutter4, Daan Christiaens4, Maximilian Pietsch4, Jakki Brandon4, Emer J Hughes4, Joanna Allsop4, Camilla O'Keeffe4, Anthony N Price4, Lucilio Cordero-Grande4, Andreas Schuh8, Antonios Makropoulos8, Jonathan Passerat-Palmbach8, Jelena Bozek9, Daniel Rueckert8, Joseph V Hajnal4, Armin Raznahan5, Grainne McAlonan1,2,3,10, A David Edwards1,4, Jonathan O'Muircheartaigh1,2,3,4.   

Abstract

Interruptions to neurodevelopment during the perinatal period may have long-lasting consequences. However, to be able to investigate deviations in the foundation of proper connectivity and functional circuits, we need a measure of how this architecture evolves in the typically developing brain. To this end, in a cohort of 241 term-born infants, we used magnetic resonance imaging to estimate cortical profiles based on morphometry and microstructure over the perinatal period (37-44 weeks postmenstrual age, PMA). Using the covariance of these profiles as a measure of inter-areal network similarity (morphometric similarity networks; MSN), we clustered these networks into distinct modules. The resulting modules were consistent and symmetric, and corresponded to known functional distinctions, including sensory-motor, limbic, and association regions, and were spatially mapped onto known cytoarchitectonic tissue classes. Posterior regions became more morphometrically similar with increasing age, while peri-cingulate and medial temporal regions became more dissimilar. Network strength was associated with age: Within-network similarity increased over age suggesting emerging network distinction. These changes in cortical network architecture over an 8-week period are consistent with, and likely underpin, the highly dynamic processes occurring during this critical period. The resulting cortical profiles might provide normative reference to investigate atypical early brain development.
© The Author(s) 2020. Published by Oxford University Press.

Entities:  

Keywords:  developing brain; morphometric similarity networks; multimodal MRI; perinatal; structural covariance

Mesh:

Year:  2020        PMID: 32537627      PMCID: PMC7673474          DOI: 10.1093/cercor/bhaa150

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


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