Literature DB >> 26956908

Subject-level measurement of local cortical coupling.

Simon N Vandekar1, Russell T Shinohara2, Armin Raznahan3, Ryan D Hopson4, David R Roalf4, Kosha Ruparel4, Ruben C Gur5, Raquel E Gur6, Theodore D Satterthwaite4.   

Abstract

The human cortex is highly folded to allow for a massive expansion of surface area. Notably, the thickness of the cortex strongly depends on cortical topology, with gyral cortex sometimes twice as thick as sulcal cortex. We recently demonstrated that global differences in thickness between gyral and sulcal cortex continue to evolve throughout adolescence. However, human cortical development is spatially heterogeneous, and global comparisons lack power to detect localized differences in development or psychopathology. Here we extend previous work by proposing a new measure - local cortical coupling - that is sensitive to differences in the localized topological relationship between cortical thickness and sulcal depth. After estimation, subject-level coupling maps can be analyzed using standard neuroimaging analysis tools. Capitalizing on a large cross-sectional sample (n=932) of youth imaged as part of the Philadelphia Neurodevelopmental Cohort, we demonstrate that local coupling is spatially heterogeneous and exhibits nonlinear development-related trajectories. Moreover, we uncover sex differences in coupling that indicate divergent patterns of cortical topology. Developmental changes and sex differences in coupling support its potential as a neuroimaging phenotype for investigating neuropsychiatric disorders that are increasingly conceptualized as disorders of brain development. R code to estimate subject-level coupling maps from any two cortical surfaces generated by FreeSurfer is made publicly available along with this manuscript.
Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Adolescence; Cortex; Cortical thickness; Development; Folding; Gyrification; MRI

Mesh:

Year:  2016        PMID: 26956908      PMCID: PMC4889557          DOI: 10.1016/j.neuroimage.2016.03.002

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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