Literature DB >> 29228120

Exploring Individual Brain Variability during Development based on Patterns of Maturational Coupling of Cortical Thickness: A Longitudinal MRI Study.

Budhachandra S Khundrakpam1,2, John D Lewis1,2, Seun Jeon1,2, Penelope Kostopoulos1,2, Yasser Itturia Medina1,2, François Chouinard-Decorte1,2, Alan C Evans1,2.   

Abstract

Structural covariance has recently emerged as a tool to study brain connectivity in health and disease. The main assumption behind the phenomenon of structural covariance is that changes in brain structure during development occur in a coordinated fashion. However, no study has yet explored the correlation of structural brain changes within individuals across development. Here, we used longitudinal magnetic resonance imaging scans from 141 normally developing children and adolescents (scanned 3 times) to introduce a novel subject-based maturational coupling approach. For each subject, maturational coupling was defined as similarity in the trajectory of cortical thickness (across the time points) between any two cortical regions. Our approach largely captured features seen in population-based structural covariance, and confirmed strong maturational coupling between homologous and near-neighbor cortical regions. Stronger maturational coupling among several homologous regions was observed for females compared to males, possibly indicating greater interhemispheric connectivity in females. Developmental changes in maturational coupling within the default-mode network (DMN) aligned with developmental changes in structural and functional DMN connectivity. Our findings indicate that patterns of maturational coupling within individuals may provide mechanistic explanation for the phenomenon of structural covariance, and allow investigation of individual brain variability with respect to cognition and disease vulnerability.

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Year:  2019        PMID: 29228120     DOI: 10.1093/cercor/bhx317

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


  10 in total

1.  Structural Variability in the Human Brain Reflects Fine-Grained Functional Architecture at the Population Level.

Authors:  Stephen Smith; Eugene Duff; Adrian Groves; Thomas E Nichols; Saad Jbabdi; Lars T Westlye; Christian K Tamnes; Andreas Engvig; Kristine B Walhovd; Anders M Fjell; Heidi Johansen-Berg; Gwenaëlle Douaud
Journal:  J Neurosci       Date:  2019-05-31       Impact factor: 6.167

2.  Altered Sex Chromosome Dosage Induces Coordinated Shifts in Cortical Anatomy and Anatomical Covariance.

Authors:  Anastasia Xenophontos; Jakob Seidlitz; Siyuan Liu; Liv S Clasen; Jonathan D Blumenthal; Jay N Giedd; Aaron Alexander-Bloch; Armin Raznahan
Journal:  Cereb Cortex       Date:  2020-04-14       Impact factor: 5.357

3.  Brain morphometric similarity and flexibility.

Authors:  Vesna Vuksanović
Journal:  Cereb Cortex Commun       Date:  2022-06-16

4.  Early-life stress exposure and large-scale covariance brain networks in extremely preterm-born infants.

Authors:  Femke Lammertink; Martijn P van den Heuvel; Erno J Hermans; Jeroen Dudink; Maria L Tataranno; Manon J N L Benders; Christiaan H Vinkers
Journal:  Transl Psychiatry       Date:  2022-06-18       Impact factor: 7.989

5.  Screen media activity and brain structure in youth: Evidence for diverse structural correlation networks from the ABCD study.

Authors:  Martin P Paulus; Lindsay M Squeglia; Kara Bagot; Joanna Jacobus; Rayus Kuplicki; Florence J Breslin; Jerzy Bodurka; Amanda Sheffield Morris; Wesley K Thompson; Hauke Bartsch; Susan F Tapert
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6.  Disruption and Compensation of Sulcation-based Covariance Networks in Neonatal Brain Growth after Perinatal Injury.

Authors:  Sharon Y Kim; Mengting Liu; Seok-Jun Hong; Arthur W Toga; A James Barkovich; Duan Xu; Hosung Kim
Journal:  Cereb Cortex       Date:  2020-11-03       Impact factor: 5.357

7.  Longitudinal cortical network reorganization in early relapsing-remitting multiple sclerosis.

Authors:  Vinzenz Fleischer; Nabin Koirala; Amgad Droby; René-Maxime Gracien; Ralf Deichmann; Ulf Ziemann; Sven G Meuth; Muthuraman Muthuraman; Frauke Zipp; Sergiu Groppa
Journal:  Ther Adv Neurol Disord       Date:  2019-04-24       Impact factor: 6.570

Review 8.  Machine Learning Methods for Diagnosing Autism Spectrum Disorder and Attention- Deficit/Hyperactivity Disorder Using Functional and Structural MRI: A Survey.

Authors:  Taban Eslami; Fahad Almuqhim; Joseph S Raiker; Fahad Saeed
Journal:  Front Neuroinform       Date:  2021-01-20       Impact factor: 4.081

9.  Towards understanding neurocognitive mechanisms of parenting: Maternal behaviors and structural brain network organization in late childhood.

Authors:  Sally Richmond; Richard Beare; Katherine A Johnson; Nicholas B Allen; Marc L Seal; Sarah Whittle
Journal:  Hum Brain Mapp       Date:  2021-02-02       Impact factor: 5.038

10.  Maturation of cortical microstructure and cognitive development in childhood and adolescence: A T1w/T2w ratio MRI study.

Authors:  Linn B Norbom; Jaroslav Rokicki; Dag Alnaes; Tobias Kaufmann; Nhat Trung Doan; Ole A Andreassen; Lars T Westlye; Christian K Tamnes
Journal:  Hum Brain Mapp       Date:  2020-08-03       Impact factor: 5.038

  10 in total

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